G-Index

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

G

ga - Variable in class burlap.behavior.singleagent.planning.ActionTransitions
ga - Variable in class burlap.behavior.singleagent.Policy.ActionProb: The action to be considered.
ga - Variable in class burlap.behavior.singleagent.vfa.ActionApproximationResult: The grounded action this approximation was for
ga - Variable in class burlap.behavior.singleagent.vfa.cmac.FVCMACFeatureDatabase.ActionFeatureID
gaListWrapper(AbstractGroundedAction) - Method in class burlap.behavior.singleagent.learning.lspi.LSPI: Wraps a GroundedAction in a list of size 1.
GameAnalysis - Class in burlap.behavior.stochasticgame: This class provides a means to record all the interactions in a stochastic game; specifically, the sequence of states, joint actions taken, and joint reward received.
GameAnalysis() - Constructor for class burlap.behavior.stochasticgame.GameAnalysis: Initialzes the datastructures.
GameAnalysis(State) - Constructor for class burlap.behavior.stochasticgame.GameAnalysis: Initializes with an initial state of the game.
gameHeight - Static variable in class burlap.domain.singleagent.frostbite.FrostbiteDomain: Game parameters
gameIceHeight - Static variable in class burlap.domain.singleagent.frostbite.FrostbiteDomain
GameSequenceVisualizer - Class in burlap.behavior.stochasticgame: This class is used to visualize a set of games that have been saved to files in a common directory or which are provided to the object as a list of GameAnalysis objects.
GameSequenceVisualizer(Visualizer, SGDomain, StateParser, String) - Constructor for class burlap.behavior.stochasticgame.GameSequenceVisualizer: Initializes the GameSequenceVisualizer.
GameSequenceVisualizer(Visualizer, SGDomain, List<GameAnalysis>) - Constructor for class burlap.behavior.stochasticgame.GameSequenceVisualizer: Initializes the GameSequenceVisualizer with programmatially supplied list of GameAnalysis objects to view.
GameSequenceVisualizer(Visualizer, SGDomain, StateParser, String, int, int) - Constructor for class burlap.behavior.stochasticgame.GameSequenceVisualizer: Initializes the GameSequenceVisualizer.
GameSequenceVisualizer(Visualizer, SGDomain, List<GameAnalysis>, int, int) - Constructor for class burlap.behavior.stochasticgame.GameSequenceVisualizer: Initializes the GameSequenceVisualizer with programmatially supplied list of GameAnalysis objects to view.
gameStarting() - Method in class burlap.behavior.stochasticgame.agents.interfacing.singleagent.SingleAgentInterface
gameStarting() - Method in class burlap.behavior.stochasticgame.agents.maql.MultiAgentQLearning
gameStarting() - Method in class burlap.behavior.stochasticgame.agents.mavf.MultiAgentVFPlanningAgent
gameStarting() - Method in class burlap.behavior.stochasticgame.agents.naiveq.history.SGQWActionHistory
gameStarting() - Method in class burlap.behavior.stochasticgame.agents.naiveq.SGNaiveQLAgent
gameStarting() - Method in class burlap.behavior.stochasticgame.agents.RandomAgent
gameStarting() - Method in class burlap.behavior.stochasticgame.agents.SetStrategyAgent
gameStarting() - Method in class burlap.behavior.stochasticgame.agents.twoplayer.repeatedsinglestage.GrimTrigger
gameStarting() - Method in class burlap.behavior.stochasticgame.agents.twoplayer.repeatedsinglestage.TitForTat
gameStarting() - Method in class burlap.behavior.stochasticgame.agents.twoplayer.singlestage.equilibriumplayer.EquilibriumPlayingAgent
gameStarting() - Method in class burlap.oomdp.stochasticgames.Agent: This method is called by the world when a new game is starting.
gameTerminated() - Method in class burlap.behavior.stochasticgame.agents.interfacing.singleagent.SingleAgentInterface
gameTerminated() - Method in class burlap.behavior.stochasticgame.agents.maql.MultiAgentQLearning
gameTerminated() - Method in class burlap.behavior.stochasticgame.agents.mavf.MultiAgentVFPlanningAgent
gameTerminated() - Method in class burlap.behavior.stochasticgame.agents.naiveq.SGNaiveQLAgent
gameTerminated() - Method in class burlap.behavior.stochasticgame.agents.RandomAgent
gameTerminated() - Method in class burlap.behavior.stochasticgame.agents.SetStrategyAgent
gameTerminated() - Method in class burlap.behavior.stochasticgame.agents.twoplayer.repeatedsinglestage.GrimTrigger
gameTerminated() - Method in class burlap.behavior.stochasticgame.agents.twoplayer.repeatedsinglestage.TitForTat
gameTerminated() - Method in class burlap.behavior.stochasticgame.agents.twoplayer.singlestage.equilibriumplayer.EquilibriumPlayingAgent
gameTerminated() - Method in class burlap.oomdp.stochasticgames.Agent: This method is called by the world when a game has ended.
gameWidth - Static variable in class burlap.domain.singleagent.frostbite.FrostbiteDomain
gamma - Variable in class burlap.behavior.singleagent.learnbydemo.IRLRequest: The discount factor of the problem
gamma - Variable in class burlap.behavior.singleagent.learning.actorcritic.critics.TDLambda: The discount factor
gamma - Variable in class burlap.behavior.singleagent.learning.modellearning.modelplanners.VIModelPlanner: The model planning discount factor
gamma - Variable in class burlap.behavior.singleagent.planning.OOMDPPlanner: The discount factor
GaussianRBF - Class in burlap.behavior.singleagent.vfa.rbf.functions: An RBF whose response is dictated by a Gaussian kernel.
GaussianRBF(State, DistanceMetric, double) - Constructor for class burlap.behavior.singleagent.vfa.rbf.functions.GaussianRBF: Initializes with a center state, a distance metric and a bandwidth parameter.
gc - Variable in class burlap.behavior.singleagent.learning.GoalBasedRF
gc - Variable in class burlap.behavior.singleagent.planning.deterministic.DeterministicPlanner: This State condition test should return true for goal states and false for non-goal states.
gc - Variable in class burlap.behavior.singleagent.planning.deterministic.UniformPlusGoalRF
GDSLInit(Domain, RewardFunction, TerminalFunction, double, ValueFunctionApproximation, double, Policy, int, double) - Method in class burlap.behavior.singleagent.learning.tdmethods.vfa.GradientDescentSarsaLam: Initializes SARSA(\lambda) By default the agent will only save the last learning episode and a call to the GradientDescentSarsaLam.planFromState(State) method will cause the planner to use only one episode for planning; this should probably be changed to a much larger value if you plan on using this algorithm as a planning algorithm.
GeneralBimatrixSolverTools - Class in burlap.behavior.stochasticgame.solvers: A class holding static methods for performing common operations on bimatrix games.
GeneralBimatrixSolverTools() - Constructor for class burlap.behavior.stochasticgame.solvers.GeneralBimatrixSolverTools
generate(GroundedAction) - Method in class burlap.behavior.singleagent.planning.stochastic.montecarlo.uct.UCTActionNode.UCTActionConstructor: Returns a UCTActionNode Object that wraps the given action
generate(StateHashTuple, int, List<Action>, UCTActionNode.UCTActionConstructor) - Method in class burlap.behavior.singleagent.planning.stochastic.montecarlo.uct.UCTStateNode.UCTStateConstructor: Generates an instance of a UCTStateNode
generateAgent() - Method in interface burlap.behavior.singleagent.learning.LearningAgentFactory: Generates a new LearningAgent object and returns it.
generateAgent() - Method in class burlap.behavior.stochasticgame.agents.maql.MAQLFactory
generateAgent() - Method in class burlap.behavior.stochasticgame.agents.mavf.MAVFPlanAgentFactory
generateAgent() - Method in class burlap.behavior.stochasticgame.agents.naiveq.history.SGQWActionHistoryFactory
generateAgent() - Method in class burlap.behavior.stochasticgame.agents.naiveq.SGNaiveQFactory
generateAgent() - Method in class burlap.behavior.stochasticgame.agents.SetStrategyAgent.SetStrategyAgentFactory
generateAgent() - Method in class burlap.behavior.stochasticgame.agents.twoplayer.repeatedsinglestage.GrimTrigger.GrimTriggerAgentFactory
generateAgent() - Method in class burlap.behavior.stochasticgame.agents.twoplayer.repeatedsinglestage.TitForTat.TitForTatAgentFactory
generateAgent() - Method in interface burlap.oomdp.stochasticgames.AgentFactory: Returns a new agent instance.
generateAgent() - Method in class burlap.oomdp.stochasticgames.common.AgentFactoryWithSubjectiveReward
generateAgentForRLDomain(Domain, double, RewardFunction, TerminalFunction) - Method in class burlap.behavior.singleagent.interfaces.rlglue.common.RLGlueCMACSarsaLambdaFactory
generateAgentForRLDomain(Domain, double, RewardFunction, TerminalFunction) - Method in class burlap.behavior.singleagent.interfaces.rlglue.common.RLGLueQlearningFactory
generateAgentForRLDomain(Domain, double, RewardFunction, TerminalFunction) - Method in class burlap.behavior.singleagent.interfaces.rlglue.common.RLGlueSARSALambdaFactory
generateAgentForRLDomain(Domain, double, RewardFunction, TerminalFunction) - Method in interface burlap.behavior.singleagent.interfaces.rlglue.RLGlueLearningAgentFactory: Returns a BURLAP learning agent for the given RLGlue generated domain, discount, reward function, and terminal function.
generateAgentForRLDomain(Domain, RewardFunction, TerminalFunction) - Method in interface burlap.behavior.stochasticgame.agents.interfacing.singleagent.SALearningAgentFactoryForSG: Returns a BURLAP learning agent for the given RLGlue generated domain, discount, reward function, and terminal function.
generateAllLocationSetsHelper(List<List<GridGameStandardMechanics.Location2Prob>>, int, GridGameStandardMechanics.Location2[], double, List<GridGameStandardMechanics.LocationSetProb>) - Method in class burlap.domain.stochasticgames.gridgame.GridGameStandardMechanics: This method will recursively generate all possible joint location outcomes for a list of possible outcomes for each agent
generateAllPossibleCollisionWinnerAssignments(List<List<Integer>>, int, int[], List<List<Integer>>) - Method in class burlap.domain.stochasticgames.gridgame.GridGameStandardMechanics
generateClassifier() - Method in interface burlap.behavior.singleagent.planning.vfa.fittedvi.WekaVFATrainer.WekaClassifierGenerator: Returns a Weka Classifier that can be used to for training on new data.
generateClassifier() - Method in interface burlap.datastructures.WekaInterfaces.WekaClassifierGenerator
generateCoefficientVectors() - Method in class burlap.behavior.singleagent.vfa.fourier.FourierBasis: Generates all coefficient vectors given the number of state variables and the maximum number of non-zero coefficient element entries.
generateCoefficientVectorsHelper(int, short[], int) - Method in class burlap.behavior.singleagent.vfa.fourier.FourierBasis: Recursive cofficient generator helper method.
generateDifferentiablePlannerForRequest(MLIRLRequest) - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.support.QGradientPlannerFactory.DifferentiableVIFactory
generateDifferentiablePlannerForRequest(MLIRLRequest) - Method in interface burlap.behavior.singleagent.learnbydemo.mlirl.support.QGradientPlannerFactory: Returns a QGradientPlanner for an MLIRLRequest object's domain, reward function, discount factor, and Boltzmann beta parameter.
generateDomain() - Method in class burlap.behavior.singleagent.interfaces.rlglue.RLGlueWrappedDomainGenerator
generateDomain() - Method in class burlap.behavior.singleagent.learning.modellearning.ModeledDomainGenerator
generateDomain() - Method in class burlap.behavior.stochasticgame.agents.interfacing.singleagent.SGToSADomain
generateDomain() - Method in class burlap.domain.singleagent.blockdude.BlockDude
generateDomain() - Method in class burlap.domain.singleagent.blocksworld.BlocksWorld
generateDomain() - Method in class burlap.domain.singleagent.cartpole.CartPoleDomain
generateDomain() - Method in class burlap.domain.singleagent.cartpole.InvertedPendulum
generateDomain() - Method in class burlap.domain.singleagent.frostbite.FrostbiteDomain: Creates a new frostbite domain.
generateDomain() - Method in class burlap.domain.singleagent.graphdefined.GraphDefinedDomain
generateDomain() - Method in class burlap.domain.singleagent.gridworld.GridWorldDomain
generateDomain() - Method in class burlap.domain.singleagent.gridworld.macro.MacroCellGridWorld
generateDomain() - Method in class burlap.domain.singleagent.lunarlander.LunarLanderDomain
generateDomain() - Method in class burlap.domain.singleagent.mountaincar.MountainCar
generateDomain() - Method in class burlap.domain.singleagent.tabularized.TabulatedDomainWrapper
generateDomain() - Method in class burlap.domain.stochasticgames.gridgame.GridGame
generateDomain() - Method in class burlap.domain.stochasticgames.normalform.SingleStageNormalFormGame
generateDomain() - Method in interface burlap.oomdp.auxiliary.DomainGenerator: Returns a newly instanced Domain object
generateDomain() - Method in class burlap.oomdp.singleagent.environment.DomainEnvironmentWrapper
generateFeatureVectorFrom(State) - Method in class burlap.behavior.singleagent.vfa.common.ConcatenatedObjectFeatureVectorGenerator
generateFeatureVectorFrom(State) - Method in class burlap.behavior.singleagent.vfa.common.FDFeatureVectorGenerator
generateFeatureVectorFrom(State) - Method in class burlap.behavior.singleagent.vfa.common.PFFeatureVectorGenerator
generateFeatureVectorFrom(State) - Method in interface burlap.behavior.singleagent.vfa.StateToFeatureVectorGenerator: Returns a feature vector represented as a double array for a given input state.
generateGaussianRBFsForStates(List<State>, StateToFeatureVectorGenerator, FVDistanceMetric, double) - Static method in class burlap.behavior.singleagent.vfa.rbf.functions.FVGaussianRBF: Creates a List of FVGaussianRBF units for each State provided using the given StateToFeatureVectorGenerator, metric, and epsilon value.
generateGaussianRBFsForStates(List<State>, StateToFeatureVectorGenerator, double) - Static method in class burlap.behavior.singleagent.vfa.rbf.functions.FVGaussianRBF: Creates a List of FVGaussianRBF units for each State provided using the given StateToFeatureVectorGenerator, and epsilon value and using a default FVEuclideanDistance metric for all units.
generateGaussianRBFsForStates(List<State>, DistanceMetric, double) - Static method in class burlap.behavior.singleagent.vfa.rbf.functions.GaussianRBF: Creates a List of GaussianRBF units for each State provided using the given metric and epsilon value.
generateGroundedActionForState(State) - Method in class burlap.oomdp.singleagent.interfaces.rlglue.RLGlueEnvironment.ActionIndexParameterization: Returns a grounded action for a given state by finding the object instance names for the objects in the positions of this objects parameter indcies.
generateNewCurrentState() - Method in class burlap.oomdp.stochasticgames.World: Causes the world to set the current state to a state generated by the provided SGStateGenerator object.
generateOptionTerminalState(State) - Method in interface burlap.behavior.singleagent.options.DirectOptionTerminateMapper: Returns the termination state that will result from applying the option associated with this object in the given initiation state.
generateRandomMacroCellRF(PropositionalFunction[]) - Static method in class burlap.domain.singleagent.gridworld.macro.MacroCellGridWorld: Given an array of macro-cell propositional functions, returns a random reward function that is a linear combination of them.
generateRandomPolicy(Domain) - Static method in class burlap.behavior.singleagent.learnbydemo.apprenticeship.ApprenticeshipLearning.RandomPolicy
generateRandomRewardsMap(PropositionalFunction[]) - Static method in class burlap.domain.singleagent.gridworld.macro.MacroCellGridWorld: Given an array of macro-cell propositional functions, returns a random reward weight to be associated with them which can then be used to create a reward function.
generateRewardFunction(StateToFeatureVectorGenerator, ApprenticeshipLearning.FeatureWeights) - Static method in class burlap.behavior.singleagent.learnbydemo.apprenticeship.ApprenticeshipLearning: Generates an anonymous instance of a reward function derived from a FeatureMapping and associated feature weights Computes (w^(i))T phi from step 4 in section 3
generateState() - Method in class burlap.domain.singleagent.mountaincar.MCRandomStateGenerator
generateState() - Method in class burlap.oomdp.auxiliary.common.ConstantStateGenerator
generateState() - Method in class burlap.oomdp.auxiliary.common.RandomStartStateGenerator
generateState() - Method in interface burlap.oomdp.auxiliary.StateGenerator: Returns a new state object.
generateState(List<Agent>) - Method in class burlap.oomdp.stochasticgames.common.ConstantSGStateGenerator
generateState(List<Agent>) - Method in class burlap.oomdp.stochasticgames.SGStateGenerator: Generates a new state with the given agents in it.
generateVFA(double) - Method in class burlap.behavior.singleagent.vfa.cmac.CMACFeatureDatabase: After all the tiling specifications have been set, this method can be called to produce a linear VFA object.
generateVFA(double) - Method in class burlap.behavior.singleagent.vfa.cmac.FVCMACFeatureDatabase: After all the tiling specifications have been set, this method can be called to produce a linear VFA object.
generateVFA(double) - Method in class burlap.behavior.singleagent.vfa.fourier.FourierBasis: Creates and returns a linear VFA object over this Fourier basis feature database.
generateVFA(double) - Method in class burlap.behavior.singleagent.vfa.rbf.FVRBFFeatureDatabase: Creates and returns a linear VFA object over this RBF feature database.
generateVFA(double) - Method in class burlap.behavior.singleagent.vfa.rbf.RBFFeatureDatabase: Creates and returns a linear VFA object over this RBF feature database.
generateWorld() - Method in class burlap.oomdp.stochasticgames.tournament.common.ConstantWorldGenerator
generateWorld() - Method in interface burlap.oomdp.stochasticgames.WorldGenerator: Generates a new World instance.
generatingAction - Variable in class burlap.behavior.singleagent.planning.deterministic.SearchNode: The action that generated this state in the previous state.
get(int) - Method in class burlap.behavior.singleagent.learning.lspi.SARSData: Returns the SARSData.SARS tuple for the ith dataset element.
get(String) - Method in class burlap.domain.stochasticgames.normalform.SingleStageNormalFormGame.ActionNameMap
getA() - Method in class burlap.behavior.singleagent.learning.actorcritic.CritiqueResult: Returns the action of this behavior.
getActingAgentName() - Method in class burlap.behavior.stochasticgame.PolicyFromJointPolicy: Returns the acting agent's name
getAction(int) - Method in class burlap.behavior.singleagent.EpisodeAnalysis: Returns the action taken in the state at time step t.
getAction(State) - Method in class burlap.behavior.singleagent.learnbydemo.apprenticeship.ApprenticeshipLearning.RandomPolicy
getAction(State) - Method in class burlap.behavior.singleagent.learning.actorcritic.actor.BoltzmannActor
getAction(State) - Method in class burlap.behavior.singleagent.learning.modellearning.DomainMappedPolicy
getAction(State) - Method in class burlap.behavior.singleagent.learning.modellearning.rmax.UnmodeledFavoredPolicy
getAction(State) - Method in class burlap.behavior.singleagent.planning.commonpolicies.BoltzmannQPolicy
getAction(State) - Method in class burlap.behavior.singleagent.planning.commonpolicies.CachedPolicy
getAction(State) - Method in class burlap.behavior.singleagent.planning.commonpolicies.EpsilonGreedy
getAction(State) - Method in class burlap.behavior.singleagent.planning.commonpolicies.GreedyDeterministicQPolicy
getAction(State) - Method in class burlap.behavior.singleagent.planning.commonpolicies.GreedyQPolicy
getAction(State) - Method in class burlap.behavior.singleagent.planning.deterministic.DDPlannerPolicy
getAction(State) - Method in class burlap.behavior.singleagent.planning.deterministic.SDPlannerPolicy
getAction(State) - Method in class burlap.behavior.singleagent.planning.stochastic.montecarlo.uct.UCTTreeWalkPolicy
getAction(State) - Method in class burlap.behavior.singleagent.Policy: This method will return an action sampled by the policy for the given state.
getAction(State) - Method in class burlap.behavior.singleagent.Policy.RandomPolicy
getAction(State) - Method in class burlap.behavior.stochasticgame.agents.interfacing.singleagent.SingleAgentInterface
getAction(State) - Method in class burlap.behavior.stochasticgame.agents.maql.MultiAgentQLearning
getAction(State) - Method in class burlap.behavior.stochasticgame.agents.mavf.MultiAgentVFPlanningAgent
getAction(State) - Method in class burlap.behavior.stochasticgame.agents.naiveq.SGNaiveQLAgent
getAction(State) - Method in class burlap.behavior.stochasticgame.agents.RandomAgent
getAction(State) - Method in class burlap.behavior.stochasticgame.agents.SetStrategyAgent
getAction(State) - Method in class burlap.behavior.stochasticgame.agents.twoplayer.repeatedsinglestage.GrimTrigger
getAction(State) - Method in class burlap.behavior.stochasticgame.agents.twoplayer.repeatedsinglestage.TitForTat
getAction(State) - Method in class burlap.behavior.stochasticgame.agents.twoplayer.singlestage.equilibriumplayer.EquilibriumPlayingAgent
getAction(State) - Method in class burlap.behavior.stochasticgame.mavaluefunction.policies.ECorrelatedQJointPolicy
getAction(State) - Method in class burlap.behavior.stochasticgame.mavaluefunction.policies.EGreedyJointPolicy
getAction(State) - Method in class burlap.behavior.stochasticgame.mavaluefunction.policies.EGreedyMaxWellfare
getAction(State) - Method in class burlap.behavior.stochasticgame.mavaluefunction.policies.EMinMaxPolicy
getAction(State) - Method in class burlap.behavior.stochasticgame.PolicyFromJointPolicy
getAction(String) - Method in class burlap.oomdp.core.Domain: Returns the single agent action with the given name.
getAction(String) - Method in class burlap.oomdp.singleagent.SADomain
getAction(State) - Method in class burlap.oomdp.stochasticgames.Agent: This method is called by the world when it needs the agent to choose an action
getAction(String) - Method in class burlap.oomdp.stochasticgames.SGDomain
getActionApproximation(State, GroundedAction) - Method in class burlap.behavior.singleagent.learning.tdmethods.vfa.GradientDescentSarsaLam: Returns the VFA Q-value approximation for the given state and action.
getActionDistributionForState(State) - Method in class burlap.behavior.singleagent.learnbydemo.apprenticeship.ApprenticeshipLearning.RandomPolicy
getActionDistributionForState(State) - Method in class burlap.behavior.singleagent.learning.actorcritic.actor.BoltzmannActor
getActionDistributionForState(State) - Method in class burlap.behavior.singleagent.learning.modellearning.DomainMappedPolicy
getActionDistributionForState(State) - Method in class burlap.behavior.singleagent.learning.modellearning.rmax.UnmodeledFavoredPolicy
getActionDistributionForState(State, String[]) - Method in class burlap.behavior.singleagent.options.DeterminisitcTerminationOption
getActionDistributionForState(State, String[]) - Method in class burlap.behavior.singleagent.options.MacroAction
getActionDistributionForState(State, String[]) - Method in class burlap.behavior.singleagent.options.Option: Returns the option's policy distribution for a given state.
getActionDistributionForState(State, String[]) - Method in class burlap.behavior.singleagent.options.PolicyDefinedSubgoalOption
getActionDistributionForState(State, String[]) - Method in class burlap.behavior.singleagent.options.PrimitiveOption
getActionDistributionForState(State) - Method in class burlap.behavior.singleagent.planning.commonpolicies.BoltzmannQPolicy
getActionDistributionForState(State) - Method in class burlap.behavior.singleagent.planning.commonpolicies.CachedPolicy
getActionDistributionForState(State) - Method in class burlap.behavior.singleagent.planning.commonpolicies.EpsilonGreedy
getActionDistributionForState(State) - Method in class burlap.behavior.singleagent.planning.commonpolicies.GreedyDeterministicQPolicy
getActionDistributionForState(State) - Method in class burlap.behavior.singleagent.planning.commonpolicies.GreedyQPolicy
getActionDistributionForState(State) - Method in class burlap.behavior.singleagent.planning.deterministic.DDPlannerPolicy
getActionDistributionForState(State) - Method in class burlap.behavior.singleagent.planning.deterministic.SDPlannerPolicy
getActionDistributionForState(State) - Method in class burlap.behavior.singleagent.planning.stochastic.montecarlo.uct.UCTTreeWalkPolicy
getActionDistributionForState(State) - Method in class burlap.behavior.singleagent.Policy: This method will return action probability distribution defined by the policy.
getActionDistributionForState(State) - Method in class burlap.behavior.singleagent.Policy.RandomPolicy
getActionDistributionForState(State) - Method in class burlap.behavior.stochasticgame.mavaluefunction.policies.ECorrelatedQJointPolicy
getActionDistributionForState(State) - Method in class burlap.behavior.stochasticgame.mavaluefunction.policies.EGreedyJointPolicy
getActionDistributionForState(State) - Method in class burlap.behavior.stochasticgame.mavaluefunction.policies.EGreedyMaxWellfare
getActionDistributionForState(State) - Method in class burlap.behavior.stochasticgame.mavaluefunction.policies.EMinMaxPolicy
getActionDistributionForState(State) - Method in class burlap.behavior.stochasticgame.PolicyFromJointPolicy
getActionFeaturesForQueryFromSet(GroundedAction, List<ActionFeaturesQuery>) - Static method in class burlap.behavior.singleagent.vfa.ActionFeaturesQuery: Returns the ActionFeaturesQuery object from a list of ActionFeaturesQuery objects that is associated with a given action.
getActionFeaturesSets(State, List<GroundedAction>) - Method in class burlap.behavior.singleagent.vfa.cmac.CMACFeatureDatabase
getActionFeaturesSets(State, List<GroundedAction>) - Method in class burlap.behavior.singleagent.vfa.cmac.FVCMACFeatureDatabase
getActionFeaturesSets(State, List<GroundedAction>) - Method in class burlap.behavior.singleagent.vfa.common.FVToFeatureDatabase
getActionFeaturesSets(State, List<GroundedAction>) - Method in interface burlap.behavior.singleagent.vfa.FeatureDatabase: Returns non-zero action features for all of provided actions in state s.
getActionFeaturesSets(State, List<GroundedAction>) - Method in class burlap.behavior.singleagent.vfa.fourier.FourierBasis
getActionFeaturesSets(State, List<GroundedAction>) - Method in class burlap.behavior.singleagent.vfa.rbf.FVRBFFeatureDatabase
getActionFeaturesSets(State, List<GroundedAction>) - Method in class burlap.behavior.singleagent.vfa.rbf.RBFFeatureDatabase
getActionForAgent(int, String) - Method in class burlap.behavior.stochasticgame.GameAnalysis: Returns the action taken for the given agent at the given time step where t=0 refers to the joint action taken in the initial state.
getActionForId(int) - Method in interface burlap.behavior.stochasticgame.agents.naiveq.history.ActionIdMap: Returns a corresponding GroundedSingleAction for a given int value
getActionForId(int) - Method in class burlap.behavior.stochasticgame.agents.naiveq.history.ParameterNaiveActionIdMap
getActionId(GroundedSingleAction) - Method in interface burlap.behavior.stochasticgame.agents.naiveq.history.ActionIdMap: Returns an int value corresponding to the input action
getActionId(String, String[]) - Method in interface burlap.behavior.stochasticgame.agents.naiveq.history.ActionIdMap: Returns an int value corresponding to the input action name and parameters
getActionId(GroundedSingleAction) - Method in class burlap.behavior.stochasticgame.agents.naiveq.history.ParameterNaiveActionIdMap
getActionId(String, String[]) - Method in class burlap.behavior.stochasticgame.agents.naiveq.history.ParameterNaiveActionIdMap
getActionLearningRateEntry(AbstractGroundedAction) - Method in class burlap.behavior.learningrate.ExponentialDecayLR.StateWiseLearningRate: Returns the mutable double entry for the learning rate for the action for the state with which this object is associated.
getActionList() - Method in class burlap.oomdp.stochasticgames.JointAction: Returns a list of the actions in this joint action.
getActionModel() - Method in class burlap.oomdp.stochasticgames.World: Returns the JointActionModel used in this world.
getActionMultiplier(GroundedAction) - Method in class burlap.behavior.singleagent.vfa.common.FVToFeatureDatabase: This method returns the action multiplier for the specified grounded action.
getActionMultiplier(GroundedAction) - Method in class burlap.behavior.singleagent.vfa.fourier.FourierBasis: This method returns the action multiplier for the specified grounded action.
getActionMultiplier(GroundedAction) - Method in class burlap.behavior.singleagent.vfa.rbf.FVRBFFeatureDatabase: This method returns the action multiplier for the specified grounded action.
getActionMultiplier(GroundedAction) - Method in class burlap.behavior.singleagent.vfa.rbf.RBFFeatureDatabase: This method returns the action multiplier for the specified grounded action.
getActions() - Method in class burlap.behavior.singleagent.planning.OOMDPPlanner: Returns a copy of all actions this planner uses for reasoning; including added actions that are not part of the domain specification (e.g., Options).
getActions() - Method in class burlap.oomdp.core.Domain: Returns a list of the single agent actions that define this domain.
getActions() - Method in class burlap.oomdp.singleagent.SADomain
getActions() - Method in class burlap.oomdp.stochasticgames.SGDomain
getActionSequenceString() - Method in class burlap.behavior.singleagent.EpisodeAnalysis: Returns a string representing the actions taken in this episode.
getActionSequenceString(String) - Method in class burlap.behavior.singleagent.EpisodeAnalysis: Returns a string representing the actions taken in this episode.
getActionsTransitions(StateHashTuple) - Method in class burlap.behavior.singleagent.planning.ValueFunctionPlanner: Returns the stored action transitions for the given state.
getActionTimeIndexEntry(AbstractGroundedAction) - Method in class burlap.behavior.learningrate.SoftTimeInverseDecayLR.StateWiseTimeIndex: Returns the mutable int entry for the time index for the action for the state with which this object is associated.
getAgentDefinitions() - Method in class burlap.oomdp.stochasticgames.World: Returns the agent definitions for the agents registered in this world.
getAgentName() - Method in interface burlap.behavior.singleagent.learning.LearningAgentFactory: Will return a name to identify the kind of agent that will be generated by this factory.
getAgentName() - Method in class burlap.oomdp.stochasticgames.Agent: Returns this agent's name
getAgentNames() - Method in class burlap.oomdp.stochasticgames.JointAction: Returns a list of the names of all agents who are represented in this joint action.
getAgentObjectInstance(Agent) - Method in class burlap.oomdp.stochasticgames.SGStateGenerator: Creates an object instance belonging to the object class specified in the agent's AgentType data member.
getAgentsInJointPolicy() - Method in class burlap.behavior.stochasticgame.JointPolicy: Returns a map specifying the agents who contribute actions to this joint policy.
getAgentsInvolvedInGame() - Method in class burlap.behavior.stochasticgame.GameAnalysis: Returns the set of agents involved in this game
getAgentSize() - Method in class burlap.domain.singleagent.frostbite.FrostbiteDomain: Returns the agent size
getAgentSynchronizedActionSelection(String, State) - Method in class burlap.behavior.stochasticgame.JointPolicy: This method returns the action for a single agent by a synchonrized sampling of this joint policy, which enables multiple agents to query this policy object and act according to the same selected joint actions from it.
getAgentType() - Method in class burlap.oomdp.stochasticgames.Agent: Returns this agent's type
getAgentTypeForAllPlayers(SGDomain) - Static method in class burlap.domain.stochasticgames.normalform.SingleStageNormalFormGame: Returns an AgentType object that can be used by agents being associated with any player number.
getAllActionApproximations(State) - Method in class burlap.behavior.singleagent.learning.tdmethods.vfa.GradientDescentSarsaLam: Gets all Q-value VFA results for each action for a given state
getAllApplicableGroundedActions(State) - Method in class burlap.oomdp.singleagent.Action: Returns all possible groundings of this action that can be applied in the provided State.
getAllApplicableGroundedActionsFromActionList(List<Action>, State) - Static method in class burlap.oomdp.singleagent.Action: Returns all GroundedActions that are applicable in the given State for all Action objects in the provided list.
getAllGroundedActions(State) - Method in class burlap.behavior.singleagent.planning.OOMDPPlanner: Returns all grounded actions in the provided state for all the actions that this planner can use.
getAllGroundedActionsFor(Action) - Method in class burlap.oomdp.core.State: Deprecated.
getAllGroundedActionsFor(List<Action>) - Method in class burlap.oomdp.core.State: Deprecated.
getAllGroundedActionsFor(State, String) - Method in class burlap.oomdp.stochasticgames.SingleAction: Returns all possible grounded versions of this single action for a given state and acting agent.
getAllGroundedPropsFor(PropositionalFunction) - Method in class burlap.oomdp.core.State: Deprecated.
getAllGroundedPropsForState(State) - Method in class burlap.oomdp.core.PropositionalFunction: Returns all possible groundings of this PropositionalFunction for the given State
getAllGroundedPropsFromPFList(List<PropositionalFunction>, State) - Static method in class burlap.oomdp.core.PropositionalFunction: Returns all possible groundings for all of the PropositionalFunctions in the provided list for the given State.
getAllJointActions(State) - Method in class burlap.behavior.stochasticgame.JointPolicy: Returns all possible joint actions that can be taken in state s for the set of agents defined to be used in this joint policy.
getAllJointActions(State, List<Agent>) - Static method in class burlap.oomdp.stochasticgames.JointAction
getAllJointActions(State, Map<String, AgentType>) - Static method in class burlap.oomdp.stochasticgames.JointAction
getAllLocationSets(List<List<GridGameStandardMechanics.Location2Prob>>) - Method in class burlap.domain.stochasticgames.gridgame.GridGameStandardMechanics: Takes a list of possible location outcomes for each agent and generates all joint location outcomes
getAllObjects() - Method in class burlap.oomdp.core.State: Returns the list of observable and hidden object instances in this state.
getAllObjectsByTrueClass() - Method in class burlap.oomdp.core.State: Returns a list of list of object instances, grouped by object class
getAllPossibleCollisionWinnerAssignment(Map<Integer, List<Integer>>) - Method in class burlap.domain.stochasticgames.gridgame.GridGameStandardMechanics
getAllPossibleGroundedSingleActions(State, String, List<SingleAction>) - Static method in class burlap.oomdp.stochasticgames.SingleAction: Returns all possible grounded versions of the provided list of SingleAction objects that an agent can take in the given state.
getAllQGradients(State) - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.DifferentiableSparseSampling
getAllQGradients(State) - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.DifferentiableVFPlanner
getAllQGradients(State) - Method in interface burlap.behavior.singleagent.learnbydemo.mlirl.support.QGradientPlanner: Returns the list of Q-value gradients (returned as objects) for each action permissible in the given state.
getAllRelationalTargets(String) - Method in class burlap.oomdp.core.ObjectInstance: Returns the set of all relational targets to which the relational attribute named attName is set.
getAllRelationalTargets() - Method in class burlap.oomdp.core.Value: Returns the ordered set of all relational targets of this object.
getAllRelationalTargets() - Method in class burlap.oomdp.core.values.DiscreteValue
getAllRelationalTargets() - Method in class burlap.oomdp.core.values.DoubleArrayValue
getAllRelationalTargets() - Method in class burlap.oomdp.core.values.IntArrayValue
getAllRelationalTargets() - Method in class burlap.oomdp.core.values.IntValue
getAllRelationalTargets() - Method in class burlap.oomdp.core.values.MultiTargetRelationalValue
getAllRelationalTargets() - Method in class burlap.oomdp.core.values.RealValue
getAllRelationalTargets() - Method in class burlap.oomdp.core.values.RelationalValue
getAllRelationalTargets() - Method in class burlap.oomdp.core.values.StringValue
getAllStates() - Method in class burlap.behavior.singleagent.planning.ValueFunctionPlanner: This method will return all states that are stored in this planners value function.
getAllStoredLearningEpisodes() - Method in class burlap.behavior.singleagent.learning.actorcritic.ActorCritic
getAllStoredLearningEpisodes() - Method in interface burlap.behavior.singleagent.learning.LearningAgent: Returns all saved EpisodeAnalysis objects of which the agent has kept track.
getAllStoredLearningEpisodes() - Method in class burlap.behavior.singleagent.learning.LearningAgent.LearningAgentBookKeeping: Returns all saved EpisodeAnalysis objects of which the agent has kept track.
getAllStoredLearningEpisodes() - Method in class burlap.behavior.singleagent.learning.lspi.LSPI
getAllStoredLearningEpisodes() - Method in class burlap.behavior.singleagent.learning.modellearning.artdp.ARTDP
getAllStoredLearningEpisodes() - Method in class burlap.behavior.singleagent.learning.modellearning.rmax.PotentialShapedRMax
getAllStoredLearningEpisodes() - Method in class burlap.behavior.singleagent.learning.tdmethods.QLearning
getAllStoredLearningEpisodes() - Method in class burlap.behavior.singleagent.learning.tdmethods.vfa.GradientDescentSarsaLam
getAllSuccessors() - Method in class burlap.behavior.singleagent.planning.stochastic.montecarlo.uct.UCTActionNode: Returns a list of all successor nodes observed
getAllUnsetAttributes() - Method in class burlap.oomdp.core.State: Returns a mapping from object instance names to the list of attributes names that have unset values.
getAnginc() - Method in class burlap.domain.singleagent.lunarlander.LunarLanderDomain: Returns how many radians the agent will rotate from its current orientation when a turn/rotate action is applied
getAnginc() - Method in class burlap.domain.singleagent.lunarlander.LunarLanderDomain.LLPhysicsParams
getAngle2ndDeriv(double, double, double, double, double, CartPoleDomain.CPPhysicsParams) - Static method in class burlap.domain.singleagent.cartpole.CartPoleDomain: Computes the 2nd order derivative of the angle for a given normal force sign using the corrected model.
getAngmax() - Method in class burlap.domain.singleagent.lunarlander.LunarLanderDomain: Returns the maximum rotate angle (in radians) that the lander can be rotated from the vertical orientation in either clockwise or counterclockwise direction.
getAngmax() - Method in class burlap.domain.singleagent.lunarlander.LunarLanderDomain.LLPhysicsParams
getApproximationResultFrom(List<StateFeature>) - Method in class burlap.behavior.singleagent.vfa.common.LinearVFA: Computes the linear function over the given features and the stored feature weights.
getAttribute(String) - Method in class burlap.oomdp.core.Domain: Returns the attribute in this domain with the given name
getAttribute(String) - Method in class burlap.oomdp.core.ObjectClass: Returns the attribute with the given name
getAttribute() - Method in class burlap.oomdp.core.Value: Returns the Attribute object for which this is a value assignment.
getAttributes() - Method in class burlap.oomdp.core.Domain: Returns a list of the attributes that define this domain.
getAvgTime() - Method in class burlap.debugtools.MyTimer: Returns the average time in seconds recorded over all start-stop calls.
getBattleOfTheSexes1() - Static method in class burlap.domain.stochasticgames.normalform.SingleStageNormalFormGame: Returns an instance of Battle of the Sexes 1, which is defined by:
(3,2); (0,0)
(0,0); (2,3)
getBattleOfTheSexes2() - Static method in class burlap.domain.stochasticgames.normalform.SingleStageNormalFormGame: Returns an instance of Battle of the Sexes 2, which is defined by:
(3,2); (1,1)
(0,0); (2,3)
getBgColor() - Method in class burlap.oomdp.visualizer.MultiLayerRenderer: Returns the background color of the renderer
getBlockAt(State, int, int) - Static method in class burlap.domain.singleagent.blockdude.BlockDude: Finds a block object in the State located at the provided position and returns its ObjectInstance.
getBoltzmannBeta() - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.MLIRLRequest
getBooleanValForAttribute(String) - Method in class burlap.oomdp.core.ObjectInstance: Returns the boolean value of the attribute (only defined for boolean attributes, int, and disc values).
getBooleanValue(String) - Method in class burlap.oomdp.core.ObjectInstance: Deprecated.
getBooleanValue() - Method in class burlap.oomdp.core.Value: Returns the boolean value of this attibute.
getBooleanValue() - Method in class burlap.oomdp.core.values.DiscreteValue
getBooleanValue() - Method in class burlap.oomdp.core.values.DoubleArrayValue
getBooleanValue() - Method in class burlap.oomdp.core.values.IntArrayValue
getBooleanValue() - Method in class burlap.oomdp.core.values.IntValue
getBooleanValue() - Method in class burlap.oomdp.core.values.MultiTargetRelationalValue
getBooleanValue() - Method in class burlap.oomdp.core.values.RealValue
getBooleanValue() - Method in class burlap.oomdp.core.values.RelationalValue
getBooleanValue() - Method in class burlap.oomdp.core.values.StringValue
getC() - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.DifferentiableSparseSampling: Returns the number of state transition samples
getC() - Method in class burlap.behavior.singleagent.planning.stochastic.sparsesampling.SparseSampling: Returns the number of state transition samples
getCartPoleStateRenderLayer() - Static method in class burlap.domain.singleagent.cartpole.CartPoleVisualizer: Returns a StateRenderLayer for cart pole.
getCartPoleVisualizer() - Static method in class burlap.domain.singleagent.cartpole.CartPoleVisualizer: Returns a visualizer for cart pole.
getCAtHeight(int) - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.DifferentiableSparseSampling: Returns the value of C for a node at the given height (height from a leaf node).
getCAtHeight(int) - Method in class burlap.behavior.singleagent.planning.stochastic.sparsesampling.SparseSampling: Returns the value of C for a node at the given height (height from a leaf node).
getChicken() - Static method in class burlap.domain.stochasticgames.normalform.SingleStageNormalFormGame: Returns an instance of Chicken, which is defined by:
(0,0); (-1,1)
(1,-1); (-10,-10)
getCI(DescriptiveStatistics, double) - Static method in class burlap.behavior.singleagent.auxiliary.performance.PerformancePlotter: Returns the confidence interval for the specified significance level
getCI(DescriptiveStatistics, double) - Static method in class burlap.behavior.stochasticgame.auxiliary.performance.MultiAgentPerformancePlotter: Returns the confidence interval for the specified significance level
getClassName() - Method in class burlap.oomdp.core.PropositionalFunction: Returns the propositional function class name of this PF.
getCleanState(Domain) - Static method in class burlap.domain.singleagent.frostbite.FrostbiteDomain: Creates a state with one agent, one igloo, and 4 rows of 4 platforms.
getCleanState(Domain, int) - Static method in class burlap.domain.singleagent.lunarlander.LunarLanderDomain: Creates a state with one agent/lander, one landing pad, and no number of obstacles.
getCleanState(Domain) - Method in class burlap.domain.singleagent.mountaincar.MountainCar: Returns a new state with the agent in the bottom of the hill valley not moving.
getCleanState(Domain, MountainCar.MCPhysicsParams) - Static method in class burlap.domain.singleagent.mountaincar.MountainCar: Returns a new state with the agent in the bottom of the hill valley not moving according to the hill design specified in the provided MountainCar.MCPhysicsParams
getCleanState(Domain, int, int, int, int, int, int) - Static method in class burlap.domain.stochasticgames.gridgame.GridGame: Returns a state with with the specified number of objects for each object class and with the specified boundary of the playing area.
getClusterPriors() - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.MultipleIntentionsMLIRL: Returns the behavior cluster prior probabilities.
getClusterRFs() - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.MultipleIntentionsMLIRL: Returns the DifferentiableRF obejcts defining each behavior cluster.
getCoefficientVector(int) - Method in class burlap.behavior.singleagent.vfa.fourier.FourierBasis: Returns the coefficient vector for the given basis function index.
getColissionSets(List<GridGameStandardMechanics.Location2>) - Method in class burlap.domain.stochasticgames.gridgame.GridGameStandardMechanics: Returns with whom each agent is in a collision competition for a cell.
getCollisionReward() - Method in class burlap.domain.singleagent.lunarlander.LunarLanderRF
getColorForString(String) - Method in class burlap.domain.singleagent.blocksworld.BlocksWorldVisualizer.BlockPainter
getColPlayersStrategy(double[][]) - Static method in class burlap.behavior.stochasticgame.solvers.MinMaxSolver: Computes the minmax strategy for the column player of the given payoff matrix.
getCompleteStateDescription() - Method in class burlap.oomdp.core.State: Returns a string representation of this state using observable and hidden object instances.
getCompleteStateDescriptionWithUnsetAttributesAsNull() - Method in class burlap.oomdp.core.State: Returns a string description of the state with unset attribute values listed as null.
getComputedPolicy() - Method in class burlap.behavior.singleagent.planning.stochastic.policyiteration.PolicyIteration: Returns the policy that was last computed.
getConsoleText(State) - Method in class burlap.oomdp.singleagent.explorer.VisualExplorer: Returns the text that will be printed to the console for the given input state.
getConsoleText(State) - Method in class burlap.oomdp.stochasticgames.explorers.SGVisualExplorer: Returns the text that will be printed to the console for the given input state.
getControlDepth() - Method in class burlap.behavior.singleagent.planning.vfa.fittedvi.FittedVI: Returns the Bellman operator depth used for computing Q-values (the FittedVI.getQ(burlap.oomdp.core.State, burlap.oomdp.core.AbstractGroundedAction) and FittedVI.getQ(burlap.oomdp.core.State, burlap.oomdp.core.AbstractGroundedAction) methods).
getCopyOfValueFunction() - Method in class burlap.behavior.singleagent.planning.ValueFunctionPlanner
getCorrdinationGameInitialState(Domain) - Static method in class burlap.domain.stochasticgames.gridgame.GridGame: Returns the initial state for a classic coordination game, where the agent's personal goals are on opposite sides.
getCorrelatedEQJointStrategy(CorrelatedEquilibriumSolver.CorrelatedEquilibriumObjective, double[][], double[][]) - Static method in class burlap.behavior.stochasticgame.solvers.CorrelatedEquilibriumSolver: Returns the correlated equilibrium joint strategy in a 2D double matrix, which represents the probability of each joint actino (where rows are player 1s actions and columns are player 2's actions).
getCorrelatedEQJointStrategyEgalitarian(double[][], double[][]) - Static method in class burlap.behavior.stochasticgame.solvers.CorrelatedEquilibriumSolver: Returns the correlated equilibrium joint strategy in a 2D double matrix for the Egalitarian objective.
getCorrelatedEQJointStrategyLibertarianForCol(double[][], double[][]) - Static method in class burlap.behavior.stochasticgame.solvers.CorrelatedEquilibriumSolver: Returns the correlated equilibrium joint strategy in a 2D double matrix for the Libertarian objective.
getCorrelatedEQJointStrategyLibertarianForRow(double[][], double[][]) - Static method in class burlap.behavior.stochasticgame.solvers.CorrelatedEquilibriumSolver: Returns the correlated equilibrium joint strategy in a 2D double matrix for the Libertarian objective.
getCorrelatedEQJointStrategyRepublican(double[][], double[][]) - Static method in class burlap.behavior.stochasticgame.solvers.CorrelatedEquilibriumSolver: Returns the correlated equilibrium joint strategy in a 2D double matrix for the Republican objective.
getCorrelatedEQJointStrategyUsingJOptimizer(double[][], double[][]) - Static method in class burlap.behavior.stochasticgame.solvers.CorrelatedEquilibriumSolver: Deprecated.
getCorrelatedEQJointStrategyUtilitarian(double[][], double[][]) - Static method in class burlap.behavior.stochasticgame.solvers.CorrelatedEquilibriumSolver: Returns the correlated equilibrium joint strategy in a 2D double matrix for the Utilitarian objective.
getCritique() - Method in class burlap.behavior.singleagent.learning.actorcritic.CritiqueResult: Returns the critique of this behavior.
getCumulativeReward(State, State, RewardFunction, double) - Method in interface burlap.behavior.singleagent.options.DirectOptionTerminateMapper: Returns the cumulative discounted reward that would be received from applying the option associated with this object in the given initiation state.
getCumulativeRewardFor(int) - Method in class burlap.oomdp.stochasticgames.tournament.Tournament: Returns the cumulative reward received by the agent who is indexed at position i
getCumulativeRewardForAgent(String) - Method in class burlap.oomdp.stochasticgames.World: Returns the cumulative reward that the agent with name aname has received across all interactions in this world.
getCurrentWorldState() - Method in class burlap.oomdp.stochasticgames.World: Returns the current world state
getCurState() - Method in class burlap.oomdp.singleagent.environment.Environment: Returns the current state of the environment
getCurTime() - Method in class burlap.behavior.singleagent.learning.actorcritic.critics.TimeIndexedTDLambda: Returns the current time/depth of the current episodes
getDataset() - Method in class burlap.behavior.singleagent.learning.lspi.LSPI: Returns the dataset this object uses for LSPI
getDebugCode() - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.DifferentiableSparseSampling: Returns the debug code used for logging plan results with DPrint.
getDebugCode() - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.MLIRL: Returns the debug code used for printing to the terminal
getDebugCode() - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.MultipleIntentionsMLIRL: Returns the debug code used for printing to the terminal
getDebugCode() - Method in class burlap.behavior.singleagent.planning.OOMDPPlanner: Returns the debug code used by this planner for calls to DPrint
getDebugCode() - Method in class burlap.behavior.singleagent.planning.stochastic.sparsesampling.SparseSampling: Returns the debug code used for logging plan results with DPrint.
getDebugCode() - Method in class burlap.oomdp.core.Domain: Returns the debug code used for printing debug messages.
getDebugId() - Method in class burlap.oomdp.stochasticgames.World: This class will report execution information as games are played using the DPrint class.
getDeepCopyOfPayoutArray(SingleStageNormalFormGame.AgentPayoutFunction[]) - Static method in class burlap.domain.stochasticgames.normalform.SingleStageNormalFormGame.AgentPayoutFunction
getDefault() - Static method in class burlap.debugtools.RandomFactory: Returns the default random number generator.
getDefaultReward() - Method in class burlap.domain.singleagent.lunarlander.LunarLanderRF
getDefaultTileWidth() - Method in class burlap.behavior.singleagent.interfaces.rlglue.common.RLGlueCMACSarsaLambdaFactory
getDefaultValue(State) - Method in class burlap.behavior.singleagent.planning.ValueFunctionPlanner: Returns the default V-value to use for the state
getDefaultWeight() - Method in class burlap.behavior.singleagent.vfa.common.LinearFVVFA
getDeterministicPolicy(State, String[]) - Method in class burlap.behavior.singleagent.options.Option: This method creates a deterministic action selection probability distribution where the deterministic action to be selected with probability 1 is the one returned by the method Option.getDeterministicPolicy(State, String[]).
getDeterministicPolicy(State) - Method in class burlap.behavior.singleagent.Policy: A helper method for defining deterministic policies.
getDiscountedReturn(double) - Method in class burlap.behavior.singleagent.EpisodeAnalysis: Will return the discounted return received from the first state in the episode to the last state in the episode.
getDiscrteizedValue(Attribute, double) - Method in class burlap.behavior.statehashing.DiscretizingStateHashFactory.DiscretizedStateHashTuple
getDiscVal() - Method in class burlap.oomdp.core.Value: Returns the discrete integer value of this Value object
getDiscVal() - Method in class burlap.oomdp.core.values.DiscreteValue
getDiscVal() - Method in class burlap.oomdp.core.values.DoubleArrayValue
getDiscVal() - Method in class burlap.oomdp.core.values.IntArrayValue
getDiscVal() - Method in class burlap.oomdp.core.values.IntValue
getDiscVal() - Method in class burlap.oomdp.core.values.MultiTargetRelationalValue
getDiscVal() - Method in class burlap.oomdp.core.values.RealValue
getDiscVal() - Method in class burlap.oomdp.core.values.RelationalValue
getDiscVal() - Method in class burlap.oomdp.core.values.StringValue
getDiscValForAttribute(String) - Method in class burlap.oomdp.core.ObjectInstance: Deprecated.
getDomain() - Method in class burlap.behavior.singleagent.learnbydemo.apprenticeship.ApprenticeshipLearningRequest
getDomain() - Method in class burlap.behavior.singleagent.learnbydemo.IRLRequest
getDomain() - Method in class burlap.behavior.singleagent.planning.OOMDPPlanner
getDomain() - Method in class burlap.oomdp.singleagent.Action: Returns the domain to which this action belongs.
getDoubleArray() - Method in class burlap.oomdp.core.Value: Returns a double array value
getDoubleArray() - Method in class burlap.oomdp.core.values.DiscreteValue
getDoubleArray() - Method in class burlap.oomdp.core.values.DoubleArrayValue
getDoubleArray() - Method in class burlap.oomdp.core.values.IntArrayValue
getDoubleArray() - Method in class burlap.oomdp.core.values.IntValue
getDoubleArray() - Method in class burlap.oomdp.core.values.MultiTargetRelationalValue
getDoubleArray() - Method in class burlap.oomdp.core.values.RealValue
getDoubleArray() - Method in class burlap.oomdp.core.values.RelationalValue
getDoubleArray() - Method in class burlap.oomdp.core.values.StringValue
getDoubleArrayValForAttribute(String) - Method in class burlap.oomdp.core.ObjectInstance: Returns the int array value of the attribute (only defined for int array attributes).
getDoubleArrayValue(String) - Method in class burlap.oomdp.core.ObjectInstance: Deprecated.
getEgalitarianObjective(double[][], double[][]) - Static method in class burlap.behavior.stochasticgame.solvers.CorrelatedEquilibriumSolver: Returns the egalitarian objective for the given payoffs for the row and column player.
getEnumeratedID(State) - Method in class burlap.behavior.singleagent.auxiliary.StateEnumerator: Get or create and get the enumeration id for a state
getEnumeratedID(StateHashTuple) - Method in class burlap.behavior.singleagent.auxiliary.StateEnumerator: Get or create and get the enumeration id for a hashed state
getEnvironmentRewardRFWrapper() - Method in class burlap.oomdp.singleagent.environment.Environment: Returns a reward function whose reward value is always whatever the last reward value of the environment is, regardless of which state, action, state parameters are passed to it.
getEnvironmentTerminalStateTFWrapper() - Method in class burlap.oomdp.singleagent.environment.Environment: Returns a terminal function that returns true when the current state of the environment is terminal, regardless of the state parameter passed to the method.
getEpisodeWeights() - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.MLIRLRequest: Returns expert episodes weights.
getEpsilon() - Method in class burlap.behavior.singleagent.learnbydemo.apprenticeship.ApprenticeshipLearningRequest
getEpsilon() - Method in class burlap.behavior.singleagent.planning.commonpolicies.EpsilonGreedy: Returns the epsilon value, where epsilon is the probability of taking a random action.
getExpectedRewards(State, String[]) - Method in class burlap.behavior.singleagent.options.Option: Returns the expected reward to be received from initiating this option from state s.
getExpertEpisodes() - Method in class burlap.behavior.singleagent.learnbydemo.apprenticeship.ApprenticeshipLearningRequest
getExpertEpisodes() - Method in class burlap.behavior.singleagent.learnbydemo.IRLRequest
getFd() - Method in class burlap.behavior.singleagent.vfa.common.FDFeatureVectorGenerator
getFeatureDatabase() - Method in class burlap.behavior.singleagent.learning.lspi.LSPI: Returns the feature database defining state features
getFeatureGenerator() - Method in class burlap.behavior.singleagent.learnbydemo.apprenticeship.ApprenticeshipLearningRequest
getFeatureWiseLearningRate(int) - Method in class burlap.behavior.learningrate.ExponentialDecayLR: Returns the learning rate data structure for the given state feature.
getFeatureWiseTimeIndex(int) - Method in class burlap.behavior.learningrate.SoftTimeInverseDecayLR: Returns the learning rate data structure for the given state feature.
getFirstObjectOfClass(String) - Method in class burlap.oomdp.core.State: Returns the first indexed object of the object class named oclass
getFlag(int) - Static method in class burlap.debugtools.DebugFlags: Returns the value for a given flag; 0 if the flag has never been created/set
getFriendFoeInitialState(Domain) - Static method in class burlap.domain.stochasticgames.gridgame.GridGame: Returns the initial state for Friend Foe game.
getFunctionWeight(int) - Method in class burlap.behavior.singleagent.vfa.common.LinearFVVFA
getFunctionWeight(int) - Method in class burlap.behavior.singleagent.vfa.common.LinearVFA
getFunctionWeight(int) - Method in interface burlap.behavior.singleagent.vfa.ValueFunctionApproximation: Returns the FunctionWeight for the given function's feature id.
getFvGen() - Method in class burlap.behavior.singleagent.vfa.common.LinearFVVFA
getFVTile(double[]) - Method in class burlap.behavior.singleagent.vfa.cmac.FVTiling: Retunrs a tile for the given input vector.
getGamma() - Method in class burlap.behavior.singleagent.learnbydemo.apprenticeship.ApprenticeshipLearningRequest
getGamma() - Method in class burlap.behavior.singleagent.learnbydemo.IRLRequest
getGamma() - Method in class burlap.behavior.singleagent.planning.OOMDPPlanner: Returns gamma, the discount factor used by this planner
getGap(StateHashTuple) - Method in class burlap.behavior.singleagent.planning.stochastic.rtdp.BoundedRTDP: Returns the lower bound and upper bound value function margin/gap for the given state
getGoalCondition() - Method in class burlap.behavior.singleagent.learning.GoalBasedRF: Returns the goal condition for this reward function.
getGoalReward() - Method in class burlap.domain.singleagent.lunarlander.LunarLanderRF
getGradient(State, GroundedAction, State) - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.commonrfs.LinearStateActionDifferentiableRF
getGradient(State, GroundedAction, State) - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.commonrfs.LinearStateDifferentiableRF
getGradient(State, GroundedAction, State) - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.diffvinit.DiffVFRF
getGradient(State, GroundedAction, State) - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.diffvinit.LinearDiffRFVInit
getGradient(State, GroundedAction, State) - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.support.DifferentiableRF: Returns the gradient of the reward function for the given state transition.
getGravity() - Method in class burlap.domain.singleagent.lunarlander.LunarLanderDomain.LLPhysicsParams
getGridWorldValueFunctionVisualization(List<State>, QComputablePlanner, Policy) - Static method in class burlap.domain.singleagent.gridworld.GridWorldDomain: Creates and returns a ValueFunctionVisualizerGUI object for a grid world.
getH() - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.DifferentiableSparseSampling: Returns the height of the tree
getH() - Method in class burlap.behavior.singleagent.planning.stochastic.sparsesampling.SparseSampling: Returns the height of the tree
getHashingFactory() - Method in class burlap.behavior.singleagent.planning.OOMDPPlanner: Returns the StateHashFactory this planner uses.
getHashMap() - Method in class burlap.datastructures.HashedAggregator: Returns the HashMap that backs this object.
getHawkDove() - Static method in class burlap.domain.stochasticgames.normalform.SingleStageNormalFormGame: Returns an instance of Hawk Dove, which is defined by:
(-1,-1); (2,0)
(0,2); (1,1)
getHeight(State, ObjectInstance) - Method in class burlap.domain.singleagent.blocksworld.BlocksWorldVisualizer.BlockPainter
getHeight() - Method in class burlap.domain.singleagent.gridworld.GridWorldDomain: Returns this grid world's height
getHiddenObjectAt(int) - Method in class burlap.oomdp.core.State: Returns the hidden object instance indexed at position i
getHiddenObjects() - Method in class burlap.oomdp.core.State: Returns the list of hidden object instances in this state.
getHistoryAugmentedState(State) - Method in class burlap.behavior.stochasticgame.agents.naiveq.history.SGQWActionHistory: Takes an input state and returns an augmented state with the history of actions each agent previously took.
getHistoryLessObjectInstanceForAgent(String, int) - Method in class burlap.behavior.stochasticgame.agents.naiveq.history.SGQWActionHistory: Returns a history object instance for a given agent in which the action that was taken is unset because the episode has not last h steps.
getHistoryObjectInstanceForAgent(GroundedSingleAction, int) - Method in class burlap.behavior.stochasticgame.agents.naiveq.history.SGQWActionHistory: Returns a history object instance for the corresponding action and how far back in history it occurred
getIdentityScalar() - Method in class burlap.behavior.singleagent.learning.lspi.LSPI: Returns the initial LSPI identity matrix scalar used
getIncredibleInitialState(Domain) - Static method in class burlap.domain.stochasticgames.gridgame.GridGame: Returns the initial state for the Incredible game (a game in which player 0 can give an incredible threat).
getInitialFunctionWeight() - Method in class burlap.behavior.singleagent.interfaces.rlglue.common.RLGlueCMACSarsaLambdaFactory
getInitialState(List<EpisodeAnalysis>) - Static method in class burlap.behavior.singleagent.learnbydemo.apprenticeship.ApprenticeshipLearning: Returns the initial state of a randomly chosen episode analysis
getInitialState(Domain) - Static method in class burlap.domain.singleagent.cartpole.CartPoleDomain: Returns the default initial state: the cart centered on the track, not moving, with the pole perfectly vertical.
getInitialState(Domain, double, double, double, double) - Static method in class burlap.domain.singleagent.cartpole.CartPoleDomain: Returns an initial state with the given initial values for the cart and pole.
getInitialState(Domain) - Static method in class burlap.domain.singleagent.cartpole.InvertedPendulum: Returns an initial state with 0 angle (perfectly vertical) and 0 angle velocity.
getInitialState(Domain, double, double) - Static method in class burlap.domain.singleagent.cartpole.InvertedPendulum: Returns an initial state with the pole at the given angle and with the given angular velocity of the pole.
getInitiationTest() - Method in class burlap.behavior.singleagent.options.DeterminisitcTerminationOption: Returns the object defining the initiation states.
getInstance(State, StateToFeatureVectorGenerator, double, Instances) - Static method in class burlap.datastructures.WekaInterfaces: Creates a Weka Instance for a state by first converting the state into a feature vector and then creating the Instance to hold that feature vector with the provided target supervised output value.
getInstance(double[], double, Instances) - Static method in class burlap.datastructures.WekaInterfaces: Creates a Weka Instance from the provided feature vector and target supervised output value and adds it to the provided dataset.
getInstancesShell(State, StateToFeatureVectorGenerator, int) - Static method in class burlap.datastructures.WekaInterfaces: Creates an empty Weka dataset (Instances) that can accommodate the feature set necessary for the input state.
getInstancesShell(double[], int) - Static method in class burlap.datastructures.WekaInterfaces: Creates an empty Weka dataset (Instances) that can accommodate the provided feature vector.
getIntArray() - Method in class burlap.oomdp.core.Value: Returns an int array value
getIntArray() - Method in class burlap.oomdp.core.values.DiscreteValue
getIntArray() - Method in class burlap.oomdp.core.values.DoubleArrayValue
getIntArray() - Method in class burlap.oomdp.core.values.IntArrayValue
getIntArray() - Method in class burlap.oomdp.core.values.IntValue
getIntArray() - Method in class burlap.oomdp.core.values.MultiTargetRelationalValue
getIntArray() - Method in class burlap.oomdp.core.values.RealValue
getIntArray() - Method in class burlap.oomdp.core.values.RelationalValue
getIntArray() - Method in class burlap.oomdp.core.values.StringValue
getIntArrayValForAttribute(String) - Method in class burlap.oomdp.core.ObjectInstance: Returns the int array value of the attribute (only defined for int array attributes).
getIntArrayValue(String) - Method in class burlap.oomdp.core.ObjectInstance: Deprecated.
getInternalRewardFunction() - Method in class burlap.oomdp.stochasticgames.Agent: Returns the internal reward function used by the agent.
getIntValForAttribute(String) - Method in class burlap.oomdp.core.ObjectInstance: Returns the int value assignment for the discrete-valued attribute named attName.
getInvertedPendulumStateRenderLayer() - Static method in class burlap.domain.singleagent.cartpole.InvertedPendulumVisualizer: Returns a StateRenderLayer object for the InvertedPendulum domain.
getInvertedPendulumVisualizer() - Static method in class burlap.domain.singleagent.cartpole.InvertedPendulumVisualizer: Returns a Visualizer object for the InvertedPendulum domain.
getJAMap(State) - Method in class burlap.behavior.stochasticgame.mavaluefunction.QSourceForSingleAgent.HashBackedQSource: Returns the Map from joint actions to q-values for a given state.
getJointAction(int) - Method in class burlap.behavior.stochasticgame.GameAnalysis: Returns the joint action taken in time step t where t=0 refers to the joint action taken in the initial state.
getJointActionModel() - Method in class burlap.oomdp.stochasticgames.SGDomain: Returns the joint action model associated with this domain.
getJointActions() - Method in class burlap.behavior.stochasticgame.GameAnalysis: Returns the joint action sequence list object
getJointPolicy() - Method in class burlap.behavior.stochasticgame.PolicyFromJointPolicy: Returns the underlying joint policy
getJointReward(int) - Method in class burlap.behavior.stochasticgame.GameAnalysis: Returns the joint reward received in time step t.
getJointRewardFunction() - Method in class burlap.domain.stochasticgames.normalform.SingleStageNormalFormGame: Returns a JointReward function for this game.
getJointRewards() - Method in class burlap.behavior.stochasticgame.GameAnalysis: Returns the joint reward sequence list object
getJSONPrepared(State) - Method in class burlap.oomdp.auxiliary.common.StateJSONParser: Returns the data structure of a state that is passed to JSON.
getK() - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.MultipleIntentionsMLIRLRequest: Returns the number of clusters.
getKNNTrainer(StateToFeatureVectorGenerator, int) - Static method in class burlap.behavior.singleagent.planning.vfa.fittedvi.WekaVFATrainer: Creates a standard supervised VFA trainer that uses Weka's IBk instance-based algorithm with a KD-tree and 1-distance similarity measure.
getLambda() - Method in class burlap.behavior.singleagent.interfaces.rlglue.common.RLGlueCMACSarsaLambdaFactory
getLambda() - Method in class burlap.behavior.singleagent.interfaces.rlglue.common.RLGlueSARSALambdaFactory
getLastComputedColStrategy() - Method in class burlap.behavior.stochasticgame.agents.twoplayer.singlestage.equilibriumplayer.BimatrixEquilibriumSolver: Returns the last column player strategy computed by the BimatrixEquilibriumSolver.solve(double[][], double[][]) method.
getLastComputedRowStrategy() - Method in class burlap.behavior.stochasticgame.agents.twoplayer.singlestage.equilibriumplayer.BimatrixEquilibriumSolver: Returns the last row player strategy computed by the BimatrixEquilibriumSolver.solve(double[][], double[][]) method.
getLastCumulativeReward() - Method in class burlap.behavior.singleagent.options.Option: Returns the cumulative discounted reward received in last execution of this option.
getLastExecutionResults() - Method in class burlap.behavior.singleagent.options.Option: Returns the events from this option's last execution
getLastJointAction() - Method in class burlap.oomdp.stochasticgames.World: Returns the last joint action taken in this world; null if none have been taken yet.
getLastLearningEpisode() - Method in class burlap.behavior.singleagent.learning.actorcritic.ActorCritic
getLastLearningEpisode() - Method in interface burlap.behavior.singleagent.learning.LearningAgent: Returns the last learning episode of the agent.
getLastLearningEpisode() - Method in class burlap.behavior.singleagent.learning.LearningAgent.LearningAgentBookKeeping: Returns the last learning episode of the agent.
getLastLearningEpisode() - Method in class burlap.behavior.singleagent.learning.lspi.LSPI
getLastLearningEpisode() - Method in class burlap.behavior.singleagent.learning.modellearning.artdp.ARTDP
getLastLearningEpisode() - Method in class burlap.behavior.singleagent.learning.modellearning.rmax.PotentialShapedRMax
getLastLearningEpisode() - Method in class burlap.behavior.singleagent.learning.tdmethods.QLearning
getLastLearningEpisode() - Method in class burlap.behavior.singleagent.learning.tdmethods.vfa.GradientDescentSarsaLam
getLastNumSteps() - Method in class burlap.behavior.singleagent.learning.tdmethods.QLearning: Returns the number of steps taken in the last episode;
getLastNumSteps() - Method in class burlap.behavior.singleagent.learning.tdmethods.vfa.GradientDescentSarsaLam: Returns the number of steps taken in the last episode;
getLastNumSteps() - Method in class burlap.behavior.singleagent.options.Option: Returns the number of steps taken in the last execution of this option.
getLastReward() - Method in class burlap.oomdp.singleagent.environment.Environment: Returns the last reward returned by the environment
getLatestTrial() - Method in class burlap.behavior.stochasticgame.auxiliary.performance.MultiAgentPerformancePlotter.DatasetsAndTrials: Returns the most recent MultiAgentPerformancePlotter.Trial object
getLearnedPolicy(ApprenticeshipLearningRequest) - Static method in class burlap.behavior.singleagent.learnbydemo.apprenticeship.ApprenticeshipLearning: Computes a policy that models the expert trajectorys included in the request object.
getLearningPolicy() - Method in class burlap.behavior.singleagent.interfaces.rlglue.common.RLGlueCMACSarsaLambdaFactory
getLearningPolicy() - Method in class burlap.behavior.singleagent.interfaces.rlglue.common.RLGLueQlearningFactory
getLearningPolicy() - Method in class burlap.behavior.singleagent.learning.lspi.LSPI: The learning policy followed by the LSPI.runLearningEpisodeFrom(State) and LSPI.runLearningEpisodeFrom(State, int) methods.
getLearningRate() - Method in class burlap.behavior.singleagent.interfaces.rlglue.common.RLGlueCMACSarsaLambdaFactory
getLearningRate() - Method in class burlap.behavior.singleagent.interfaces.rlglue.common.RLGLueQlearningFactory
getLevel1(Domain) - Static method in class burlap.domain.singleagent.blockdude.BlockDudeLevelConstructor: Returns the initial State of the first level.
getLevel2(Domain) - Static method in class burlap.domain.singleagent.blockdude.BlockDudeLevelConstructor: Returns the initial State of the second level.
getLevel3(Domain) - Static method in class burlap.domain.singleagent.blockdude.BlockDudeLevelConstructor: Returns the initial State of the third level.
getLocation(State, String) - Method in class burlap.domain.stochasticgames.gridgame.GridGameStandardMechanics: Returns the x-y position of an agent stored in a Location2 object.
getMacroCellHorizontalCount() - Method in class burlap.domain.singleagent.gridworld.macro.MacroCellGridWorld: Returns the number of columns of macro-cells (cells across the x-axis)
getMacroCellPropositionalFunctions(Domain, MacroCellGridWorld) - Static method in class burlap.domain.singleagent.gridworld.macro.MacroCellGridWorld: Returns an array of the propositional functions that detect if the agent is in a macro cell.
getMacroCellVerticalCount() - Method in class burlap.domain.singleagent.gridworld.macro.MacroCellGridWorld: Returns the number of rows of macro-cells (cells across the y-axis)
getMap() - Method in class burlap.domain.singleagent.gridworld.GridWorldDomain: Returns a deep copy of the map being used for the domain
getMapped(int) - Static method in class burlap.debugtools.RandomFactory: Returns the random generator with the associated id or creates it if it does not yet exist
getMapped(String) - Static method in class burlap.debugtools.RandomFactory: Returns the random generator with the associated String id or creates it if it does not yet exist
getMatchingPennies() - Static method in class burlap.domain.stochasticgames.normalform.SingleStageNormalFormGame: Returns an instance of Matching Pennies, which is defined by:
(1,-1); (-1,1)
(-1,1); (1,-1)
getMatchingPreference(StateHashTuple, GroundedAction, BoltzmannActor.PolicyNode) - Method in class burlap.behavior.singleagent.learning.actorcritic.actor.BoltzmannActor: Returns the stored BoltzmannActor.ActionPreference that is stored in a policy node.
getMaxChange() - Method in class burlap.behavior.singleagent.learning.lspi.LSPI: The maximum change in weights required to terminate policy iteration when called from the LSPI.planFromState(State), LSPI.runLearningEpisodeFrom(State) or LSPI.runLearningEpisodeFrom(State, int) methods.
getMaxDim() - Method in class burlap.domain.stochasticgames.gridgame.GridGame: Returns the maximum dimension of the world; it's width and height.
getMaxGT() - Method in class burlap.domain.stochasticgames.gridgame.GridGame: Returns the maximum goal types
getMaxIterations() - Method in class burlap.behavior.singleagent.learnbydemo.apprenticeship.ApprenticeshipLearningRequest
getMaxLearningSteps() - Method in class burlap.behavior.singleagent.learning.lspi.LSPI: The maximum number of learning steps permitted by the LSPI.runLearningEpisodeFrom(State) method.
getMaxNumPlanningIterations() - Method in class burlap.behavior.singleagent.learning.lspi.LSPI: The maximum number of policy iterations that will be used by the LSPI.planFromState(State) method.
getMaxPlyrs() - Method in class burlap.domain.stochasticgames.gridgame.GridGame: Returns the max number of players
getMaxQ(StateHashTuple) - Method in class burlap.behavior.singleagent.learning.tdmethods.QLearning: Returns the maximum Q-value in the hashed stated.
getMaxQValue(State) - Method in class burlap.behavior.stochasticgame.agents.naiveq.SGNaiveQLAgent: Returns maximum numeric Q-value for a given state
getMaxWT() - Method in class burlap.domain.stochasticgames.gridgame.GridGame: Returns the maximum number of wall types
getMaxx() - Method in class burlap.domain.singleagent.blockdude.BlockDude
getMaxy() - Method in class burlap.domain.singleagent.blockdude.BlockDude
getMinNewStepsForLearningPI() - Method in class burlap.behavior.singleagent.learning.lspi.LSPI: The minimum number of new learning observations before policy iteration is run again.
getModel() - Method in class burlap.behavior.singleagent.learning.modellearning.rmax.PotentialShapedRMax: Returns the model learning algorithm being used.
getModeledDomain() - Method in class burlap.behavior.singleagent.learning.modellearning.rmax.PotentialShapedRMax: Returns the model domain for planning.
getModeledRewardFunction() - Method in class burlap.behavior.singleagent.learning.modellearning.rmax.PotentialShapedRMax: Returns the model reward function.
getModeledTerminalFunction() - Method in class burlap.behavior.singleagent.learning.modellearning.rmax.PotentialShapedRMax: Returns the model terminal function.
getModelPlanner(Domain, RewardFunction, TerminalFunction, double) - Method in interface burlap.behavior.singleagent.learning.modellearning.ModelPlanner.ModelPlannerGenerator
getModelPlanner(Domain, RewardFunction, TerminalFunction, double) - Method in class burlap.behavior.singleagent.learning.modellearning.modelplanners.VIModelPlanner.VIModelPlannerGenerator
getModelPlanner() - Method in class burlap.behavior.singleagent.learning.modellearning.rmax.PotentialShapedRMax: Returns the planning algorithm used on the model that can be iteratively updated as the model changes.
getModelRF() - Method in class burlap.behavior.singleagent.learning.modellearning.Model: Returns the learned reward function in this model
getModelRF() - Method in class burlap.behavior.singleagent.learning.modellearning.models.TabularModel
getModelTF() - Method in class burlap.behavior.singleagent.learning.modellearning.Model: Returns the learned terminal function in this model
getModelTF() - Method in class burlap.behavior.singleagent.learning.modellearning.models.TabularModel
getMultiLayerRenderer() - Method in class burlap.behavior.singleagent.auxiliary.valuefunctionvis.ValueFunctionVisualizerGUI: Returns the MultiLayerRenderer used in this GUI.
getMyQSource() - Method in class burlap.behavior.stochasticgame.agents.maql.MultiAgentQLearning: Returns this agent's individual Q-value source
getName() - Method in class burlap.oomdp.core.ObjectInstance: Returns the name identifier of this object instance
getName() - Method in class burlap.oomdp.core.PropositionalFunction: Returns the name of this propositional function.
getName() - Method in class burlap.oomdp.singleagent.Action: Returns the name of the action
getNegatedArray(double[]) - Static method in class burlap.behavior.stochasticgame.solvers.GeneralBimatrixSolverTools: Returns a negated version of the input array in a new array object.
getNegatedMatrix(double[][]) - Static method in class burlap.behavior.stochasticgame.solvers.GeneralBimatrixSolverTools: Returns a negated version of the input matrix in a new matrix object.
getNewDomainWithCopiedObjectClasses() - Method in class burlap.oomdp.core.Domain: This will return a new domain object populated with copies of this Domain's ObjectClasses.
getNewState(Domain, int) - Static method in class burlap.domain.singleagent.blocksworld.BlocksWorld: Creates a new state with nBlocks block objects in it.
getNewWorldNameForAgentAndIndex(Agent, AgentType) - Method in class burlap.oomdp.stochasticgames.World: Returns a unique agent name for the given agent object and agent type for that agent.
getNextMatch() - Method in class burlap.oomdp.stochasticgames.tournament.common.AllPairWiseSameTypeMS
getNextMatch() - Method in interface burlap.oomdp.stochasticgames.tournament.MatchSelector: Returns the next match information, which is a list of MatchEntry objects
getNextState(State, GroundedAction) - Method in class burlap.behavior.singleagent.planning.stochastic.rtdp.BoundedRTDP: Selects a next state for expansion when action a is applied in state s.
getNextStateByMaxMargin(State, GroundedAction) - Method in class burlap.behavior.singleagent.planning.stochastic.rtdp.BoundedRTDP: Selects a next state for expansion when action a is applied in state s according to the next possible state that has the largest lower and upper bound margin.
getNextStateBySampling(State, GroundedAction) - Method in class burlap.behavior.singleagent.planning.stochastic.rtdp.BoundedRTDP: Selects a next state for expansion when action a is applied in state s by randomly sampling from the transition dynamics weighted by the margin of the lower and upper bound value functions.
getNode(StateHashTuple) - Method in class burlap.behavior.singleagent.learning.actorcritic.actor.BoltzmannActor: Returns the policy node that stores the action preferences for state.
getNodeFor(StateHashTuple) - Method in class burlap.behavior.singleagent.planning.stochastic.valueiteration.PrioritizedSweeping: Returns or creates, stores, and returns a priority back pointer node for the given hased state
getNodeId(State) - Static method in class burlap.domain.singleagent.graphdefined.GraphDefinedDomain: Returns the state node number where the agent of the provided state is
getNodeTransitionTo(Set<GraphDefinedDomain.NodeTransitionProbibility>, int) - Method in class burlap.domain.singleagent.graphdefined.GraphDefinedDomain: Returns the GraphDefinedDomain.NodeTransitionProbibility object in the provided set that corresponds to a transition to state tNode or null if it doesn't exist.
getNormalizedObservableFeatureVec() - Method in class burlap.oomdp.core.ObjectInstance: Returns a normalized double vector of all the observable values in this object instance.
getNormForce(double, double, double, CartPoleDomain.CPPhysicsParams) - Static method in class burlap.domain.singleagent.cartpole.CartPoleDomain: Computes the normal force for the corrected model
getNSEWPolicyGlyphPainter(String, String, String, String, String, String, String) - Static method in class burlap.behavior.singleagent.auxiliary.valuefunctionvis.common.ArrowActionGlyph: Creates and returns a PolicyGlyphPainter2D where the x and y position attributes are name xAtt and yAtt, respectively, belong to the class classWithPositionAtts, and the north, south east, west actions have the corresponding names and will be rendered using ArrowActionGlyph objects.
getnTiles() - Method in class burlap.behavior.singleagent.interfaces.rlglue.common.RLGlueCMACSarsaLambdaFactory
getNumAgents() - Method in class burlap.oomdp.stochasticgames.tournament.Tournament: Returns the number of agents who are playing in this tournament
getNumberOfBellmanUpdates() - Method in class burlap.behavior.singleagent.planning.stochastic.rtdp.BoundedRTDP: Returns the total number of Bellman updates across all planning
getNumberOfBellmanUpdates() - Method in class burlap.behavior.singleagent.planning.stochastic.rtdp.RTDP: Returns the total number of Bellman updates across all planning
getNumberOfStateNodesCreated() - Method in class burlap.behavior.singleagent.planning.stochastic.sparsesampling.SparseSampling: Returns the total number of state nodes that have been created.
getNumberOfSteps() - Method in class burlap.behavior.singleagent.planning.stochastic.rtdp.BoundedRTDP: Returns the total number of planning steps that have been performed.
getNumberOfValueEsitmates() - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.DifferentiableSparseSampling: Returns the total number of state value estimates performed since the DifferentiableSparseSampling.resetPlannerResults() call.
getNumberOfValueEsitmates() - Method in class burlap.behavior.singleagent.planning.stochastic.sparsesampling.SparseSampling: Returns the total number of state value estimates performed since the SparseSampling.resetPlannerResults() call.
getNumericRepresentation() - Method in class burlap.oomdp.core.Value: Returns a numeric double representation of this value.
getNumericRepresentation() - Method in class burlap.oomdp.core.values.DiscreteValue
getNumericRepresentation() - Method in class burlap.oomdp.core.values.DoubleArrayValue
getNumericRepresentation() - Method in class burlap.oomdp.core.values.IntArrayValue
getNumericRepresentation() - Method in class burlap.oomdp.core.values.IntValue
getNumericRepresentation() - Method in class burlap.oomdp.core.values.MultiTargetRelationalValue
getNumericRepresentation() - Method in class burlap.oomdp.core.values.RealValue
getNumericRepresentation() - Method in class burlap.oomdp.core.values.RelationalValue
getNumericRepresentation() - Method in class burlap.oomdp.core.values.StringValue
getNumericValForAttribute(String) - Method in class burlap.oomdp.core.ObjectInstance: Returns the double value for the attribute named attType.
getNumNodes() - Method in class burlap.domain.singleagent.graphdefined.GraphDefinedDomain: Returns the number of state nodes specified in this domain
getNumPlayers() - Method in class burlap.domain.stochasticgames.normalform.SingleStageNormalFormGame: Returns the number of players in the domain to be generated
getNumSamplesForPlanning() - Method in class burlap.behavior.singleagent.learning.lspi.LSPI: Gets the number of SARS samples that will be gathered by the LSPI.planFromState(State) method.
getNumSteps(State, State) - Method in interface burlap.behavior.singleagent.options.DirectOptionTerminateMapper: Returns the number of steps that would have occurred for taking the option associated with this object from state s and terminating in state sp.
getNumVisited() - Method in class burlap.behavior.singleagent.planning.deterministic.uninformed.dfs.DFS: Returns the number of search nodes visited/expanded.
getObject(String) - Method in class burlap.oomdp.core.State: Returns the object in this state with the name oname
getObjectClass(String) - Method in class burlap.oomdp.core.Domain: Returns the object class in this domain with the given name.
getObjectClass() - Method in class burlap.oomdp.core.ObjectInstance: Returns this object instance's object class
getObjectClasses() - Method in class burlap.oomdp.core.Domain: Returns the list of object classes that define this domain.
getObjectClassesPresent() - Method in class burlap.oomdp.core.State: Returns a set of of the object class names for all object classes that have instantiated objects in this state.
getObjectDescription() - Method in class burlap.oomdp.core.ObjectInstance: Returns a string representation of this object including its name and value attribute value assignment.
getObjectDesriptionWithNullForUnsetAttributes() - Method in class burlap.oomdp.core.ObjectInstance: Returns a string description of the object with the unset attribute values listed as null.
getObjectMatchingTo(State, boolean) - Method in class burlap.oomdp.core.State: This method computes a matching from objects in the receiver to value-identical objects in the parameter state so.
getObjectsOfClass(String) - Method in class burlap.oomdp.core.State: Returns all objects that belong to the object class named oclass
getObjectsOfTrueClass(String) - Method in class burlap.oomdp.core.State: Deprecated.
getObservableFeatureVec() - Method in class burlap.oomdp.core.ObjectInstance: Returns a double vector of all the observable values in this object instance.
getObservableObjectAt(int) - Method in class burlap.oomdp.core.State: Returns the observable object instance indexed at position i
getObservableObjects() - Method in class burlap.oomdp.core.State: Returns the list of observable object instances in this state.
getOneAgentNLocationState(Domain, int) - Static method in class burlap.domain.singleagent.gridworld.GridWorldDomain: Will return a state object with a single agent object and n location objects
getOneAgentNoLocationState(Domain) - Static method in class burlap.domain.singleagent.gridworld.GridWorldDomain: Will return a state object with a single agent object and no location objects
getOneAgentNoLocationState(Domain, int, int) - Static method in class burlap.domain.singleagent.gridworld.GridWorldDomain: Will return a state object with a single agent object and no location objects
getOneAgentOneLocationState(Domain) - Static method in class burlap.domain.singleagent.gridworld.GridWorldDomain: Will return a state object with a single agent object and a single location object
getOpponent() - Method in class burlap.behavior.stochasticgame.agents.twoplayer.singlestage.equilibriumplayer.EquilibriumPlayingAgent: Returns the Agent object in the world for the opponent.
getOptimalValue(QComputablePlanner, State) - Static method in class burlap.behavior.singleagent.planning.QComputablePlanner.QComputablePlannerHelper: Returns the optimal state value function for a state given a QComputablePlanner.
getOptimalValue(QComputablePlanner, State, TerminalFunction) - Static method in class burlap.behavior.singleagent.planning.QComputablePlanner.QComputablePlannerHelper: Returns the optimal state value for a state given a QComputablePlanner.
getOptionsStartingWithName(String) - Method in class burlap.datastructures.CommandLineOptions: Returns the list of options whose name starts with the given option prefix.
getOrCreateActionNode(StateHashTuple, GroundedAction) - Method in class burlap.behavior.singleagent.learning.modellearning.models.TabularModel: Returns the TabularModel.StateActionNode object associated with the given hashed state and action.
getOrGenerateActionFeatureList(Map<FVTiling.FVTile, List<FVCMACFeatureDatabase.ActionFeatureID>>, FVTiling.FVTile) - Method in class burlap.behavior.singleagent.vfa.cmac.FVCMACFeatureDatabase: Returns or creates stores and returns the list of action feature ids in the given map for the given tile.
getOrGenerateFeature(Map<FVTiling.FVTile, Integer>, FVTiling.FVTile) - Method in class burlap.behavior.singleagent.vfa.cmac.FVCMACFeatureDatabase: Returns the stored feature id or creates, stores and returns one.
getOrSeedDefault(long) - Static method in class burlap.debugtools.RandomFactory: Either return a the default random generator if it has already been created; or created it with the given seed if it has not been created.
getOrSeedMapped(int, long) - Static method in class burlap.debugtools.RandomFactory: Either returns the random generator for the given id or creates if with the given seed it does not yet exit
getOrSeedMapped(String, long) - Static method in class burlap.debugtools.RandomFactory: Either returns the random generator for the given String id or creates if with the given seed it does not yet exit
getOuterTiling() - Method in class burlap.behavior.singleagent.vfa.cmac.Tiling.ObjectTile: Returns the tiling that was used to produce this object instance tile.
getOuterTiling() - Method in class burlap.behavior.singleagent.vfa.cmac.Tiling.StateTile: Returns the tiling specification that produced this tiling
getParameterClasses() - Method in class burlap.oomdp.core.PropositionalFunction: Returns the object classes of the parameters for this propositional function
getParameterClasses() - Method in class burlap.oomdp.singleagent.Action: Returns a String array of the names of of the object classes to which bound parameters must belong
getParameterDimension() - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.diffvinit.DifferentiableVInit.ParamedDiffVInit: Returns the parameter dimensionality
getParameterDimension() - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.support.DifferentiableRF: Returns the parameter dimensionality
getParameterOrderGroups() - Method in class burlap.oomdp.core.PropositionalFunction: Returns the parameter order group names for the parameters of this propositional function.
getParameterOrderGroups() - Method in class burlap.oomdp.singleagent.Action: Returns the a String array specifying the parameter order group of each parameter.
getParameters() - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.diffvinit.DifferentiableVInit.ParamedDiffVInit: Returns the parameters of this reward function.
getParameters() - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.support.DifferentiableRF: Returns the parameters of this reward function.
getPartialDerivative(int) - Method in class burlap.behavior.singleagent.vfa.WeightGradient: Returns the partial derivative for the given weight
getPayout(SingleStageNormalFormGame.StrategyProfile) - Method in class burlap.domain.stochasticgames.normalform.SingleStageNormalFormGame.AgentPayoutFunction: Returns the payout for a given strategy profile
getPayout(int, String...) - Method in class burlap.domain.stochasticgames.normalform.SingleStageNormalFormGame: Returns the payout that player pn receives for the given strategy profile.
getPayout(int, int...) - Method in class burlap.domain.stochasticgames.normalform.SingleStageNormalFormGame: Returns the payout that player pn receives for the given strategy profile.
getPersonalGoalReward(State, String) - Method in class burlap.domain.stochasticgames.gridgame.GridGame.GGJointRewardFunction: Returns the personal goal rewards.
getPFRewardWeights() - Method in class burlap.domain.singleagent.gridworld.macro.MacroCellGridWorld.LinearInPFRewardFunction
getPhysParams() - Method in class burlap.domain.singleagent.lunarlander.LunarLanderDomain.ActionIdle
getPhysParams() - Method in class burlap.domain.singleagent.lunarlander.LunarLanderDomain.ActionThrust
getPhysParams() - Method in class burlap.domain.singleagent.lunarlander.LunarLanderDomain.ActionTurn
getPhysParams() - Method in class burlap.domain.singleagent.lunarlander.LunarLanderDomain
getPlanner() - Method in class burlap.behavior.singleagent.learnbydemo.apprenticeship.ApprenticeshipLearningRequest
getPlanner() - Method in class burlap.behavior.singleagent.learnbydemo.IRLRequest
getPlannerFactory() - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.MultipleIntentionsMLIRLRequest
getPlannerInstance() - Method in class burlap.behavior.stochasticgame.agents.mavf.MAVFPlannerFactory.ConstantMAVFPlannerFactory
getPlannerInstance() - Method in interface burlap.behavior.stochasticgame.agents.mavf.MAVFPlannerFactory: returns an MAValueFunctionPlanner reference to use for planning.
getPlannerInstance() - Method in class burlap.behavior.stochasticgame.agents.mavf.MAVFPlannerFactory.MAVIPlannerFactory
getPlanningCollector() - Method in class burlap.behavior.singleagent.learning.lspi.LSPI: Gets the SARSCollector used by the LSPI.planFromState(State) method for collecting data.
getPlanningDepth() - Method in class burlap.behavior.singleagent.planning.vfa.fittedvi.FittedVI: Returns the Bellman operator depth used during planning.
getPlayerNumberForAgent(String) - Method in class burlap.oomdp.stochasticgames.World: Returns the player index for the agent with the given name.
getPolicy() - Method in class burlap.behavior.singleagent.auxiliary.valuefunctionvis.PolicyRenderLayer: Returns the policy that will be rendered.
getPolicy() - Method in class burlap.behavior.singleagent.learning.actorcritic.ActorCritic: Returns the policy/actor of this learning algorithm.
getPolicyCount() - Method in class burlap.behavior.singleagent.learnbydemo.apprenticeship.ApprenticeshipLearningRequest
getPolicyValue(QComputablePlanner, State, Policy) - Static method in class burlap.behavior.singleagent.planning.QComputablePlanner.QComputablePlannerHelper: Returns the state value under a given policy for a state and QComputablePlanner.
getPolicyValue(QComputablePlanner, State, Policy, TerminalFunction) - Static method in class burlap.behavior.singleagent.planning.QComputablePlanner.QComputablePlannerHelper: Returns the state value under a given policy for a state and QComputablePlanner.
getPolynomialDegree() - Method in class burlap.behavior.singleagent.auxiliary.valuefunctionvis.common.LandmarkColorBlendInterpolation: Returns the power to raise the normalized distance
getPositiveMatrix(double[][]) - Static method in class burlap.behavior.stochasticgame.solvers.GeneralBimatrixSolverTools: Creates a new matrix (m2) whose values are the values of m shifted by a constant amount c such that all the values in m2 are positive.
getPossibleBindingsGivenParamOrderGroups(String[], String[]) - Method in class burlap.oomdp.core.State: Given an array of parameter object classes and an array of their corresponding parameter order groups, returns all possible object instance bindings to the parameters, excluding bindings that are equivalent due to the parameter order grouping.
getPossibleCollisionOutcomes(List<GridGameStandardMechanics.Location2>, List<GridGameStandardMechanics.Location2>) - Method in class burlap.domain.stochasticgames.gridgame.GridGameStandardMechanics
getPossibleLocationsFromWallCollisions(State, GridGameStandardMechanics.Location2, GridGameStandardMechanics.Location2, List<GridGameStandardMechanics.Location2>) - Method in class burlap.domain.stochasticgames.gridgame.GridGameStandardMechanics: Returns the list of possible outcome locations for a given start point and desired position change.
getPreferences() - Method in class burlap.datastructures.BoltzmannDistribution: Returns the input preferences
getPrisonersDilemma() - Static method in class burlap.domain.stochasticgames.normalform.SingleStageNormalFormGame: Returns an instance of Prisoner's Dilemma, which is defined by:
(3,3); (0,5)
(5,0); (1,1)
getPrisonersDilemmaInitialState(Domain) - Static method in class burlap.domain.stochasticgames.gridgame.GridGame: Returns the initial state for a classic prisoner's dilemma formulated in a Grid Game.
getProbabilities() - Method in class burlap.datastructures.BoltzmannDistribution: Returns the output probability distribution.
getProbOfAction(State, AbstractGroundedAction) - Method in class burlap.behavior.singleagent.Policy: Will return the probability of this policy taking action ga in state s
getProbOfActionGivenDistribution(State, AbstractGroundedAction, List<Policy.ActionProb>) - Static method in class burlap.behavior.singleagent.Policy: Deprecated.
getProbOfActionGivenDistribution(AbstractGroundedAction, List<Policy.ActionProb>) - Static method in class burlap.behavior.singleagent.Policy: Searches the input distribution for the occurrence of the input action and returns its probability.
getPropFunction(String) - Method in class burlap.oomdp.core.Domain: Returns the propositional function in this domain with the given name
getPropFunctions() - Method in class burlap.oomdp.core.Domain: Returns a list of the propositional functions that define this domain.
getPropositionlFunctionsFromObjectClass(String) - Method in class burlap.oomdp.core.Domain: Returns a map of propositional function classes to the set of propositional functions that belong to that class, but only includes propositional function classes that define propositional functions that operate on a given object class parameter.
getPropositionlFunctionsMap() - Method in class burlap.oomdp.core.Domain: Returns a map of propositional function classes to the set of propositional functions that belong to that class.
getQ(State, AbstractGroundedAction) - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.DifferentiableSparseSampling
getQ(State, AbstractGroundedAction) - Method in class burlap.behavior.singleagent.learning.lspi.LSPI
getQ(State, AbstractGroundedAction) - Method in class burlap.behavior.singleagent.learning.modellearning.artdp.ARTDP
getQ(State, AbstractGroundedAction) - Method in class burlap.behavior.singleagent.learning.modellearning.modelplanners.VIModelPlanner
getQ(State, AbstractGroundedAction) - Method in class burlap.behavior.singleagent.learning.tdmethods.QLearning
getQ(StateHashTuple, GroundedAction) - Method in class burlap.behavior.singleagent.learning.tdmethods.QLearning: Returns the Q-value for a given hashed state and action.
getQ(State, AbstractGroundedAction) - Method in class burlap.behavior.singleagent.learning.tdmethods.vfa.GradientDescentSarsaLam
getQ(State, AbstractGroundedAction) - Method in interface burlap.behavior.singleagent.planning.QComputablePlanner: Returns the QValue for the given state-action pair.
getQ(State, AbstractGroundedAction) - Method in class burlap.behavior.singleagent.planning.stochastic.montecarlo.uct.UCT
getQ(State, AbstractGroundedAction) - Method in class burlap.behavior.singleagent.planning.stochastic.sparsesampling.SparseSampling
getQ(State, AbstractGroundedAction) - Method in class burlap.behavior.singleagent.planning.ValueFunctionPlanner
getQ(StateHashTuple, GroundedAction, Map<String, String>) - Method in class burlap.behavior.singleagent.planning.ValueFunctionPlanner: Gets a Q-Value for a hashed state, grounded action, and object instance matching from the hashed states an internally stored hashed transition dynamics.
getQ(State, AbstractGroundedAction) - Method in class burlap.behavior.singleagent.planning.vfa.fittedvi.FittedVI
getQ(State, AbstractGroundedAction) - Method in class burlap.behavior.stochasticgame.agents.naiveq.SGNaiveQLAgent
getQFromFeaturesFor(List<ActionApproximationResult>, State, GroundedAction) - Method in class burlap.behavior.singleagent.learning.lspi.LSPI: Creates a Q-value object in which the Q-value is determined from VFA.
getQFromFeaturesFor(List<ActionApproximationResult>, State, GroundedAction) - Method in class burlap.behavior.singleagent.learning.tdmethods.vfa.GradientDescentSarsaLam: Creates a Q-value object in which the Q-value is determined from VFA.
getQGradient(State, GroundedAction) - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.DifferentiableSparseSampling
getQGradient(State, GroundedAction) - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.DifferentiableVFPlanner
getQGradient(State, AbstractGroundedAction) - Method in interface burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.diffvinit.DifferentiableVInit: Returns the Q-value function gradient.
getQGradient(State, AbstractGroundedAction) - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.diffvinit.LinearDiffRFVInit
getQGradient(State, AbstractGroundedAction) - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.diffvinit.LinearStateDiffVF
getQGradient(State, AbstractGroundedAction) - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.diffvinit.VanillaDiffVinit
getQGradient(State, GroundedAction) - Method in interface burlap.behavior.singleagent.learnbydemo.mlirl.support.QGradientPlanner: Returns the Q-value gradient (QGradientTuple) for the given state and action.
getQGreedyNode(UCTStateNode) - Method in class burlap.behavior.singleagent.planning.stochastic.montecarlo.uct.UCTTreeWalkPolicy: Returns the UCTActionNode with the highest average sample return.
getqInitFunction() - Method in class burlap.behavior.singleagent.interfaces.rlglue.common.RLGLueQlearningFactory
getQs(State) - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.DifferentiableSparseSampling
getQs(State) - Method in class burlap.behavior.singleagent.learning.lspi.LSPI
getQs(State) - Method in class burlap.behavior.singleagent.learning.modellearning.artdp.ARTDP
getQs(State) - Method in class burlap.behavior.singleagent.learning.modellearning.modelplanners.VIModelPlanner
getQs(State) - Method in class burlap.behavior.singleagent.learning.tdmethods.QLearning
getQs(StateHashTuple) - Method in class burlap.behavior.singleagent.learning.tdmethods.QLearning: Returns the possible Q-values for a given hashed stated.
getQs(State) - Method in class burlap.behavior.singleagent.learning.tdmethods.vfa.GradientDescentSarsaLam
getQs(State) - Method in interface burlap.behavior.singleagent.planning.QComputablePlanner: Returns a List of QValue objects for ever permissible action for the given input state.
getQs(State) - Method in class burlap.behavior.singleagent.planning.stochastic.montecarlo.uct.UCT
getQs(State) - Method in class burlap.behavior.singleagent.planning.stochastic.sparsesampling.SparseSampling
getQs(State) - Method in class burlap.behavior.singleagent.planning.ValueFunctionPlanner
getQs(State) - Method in class burlap.behavior.singleagent.planning.vfa.fittedvi.FittedVI
getQs(State) - Method in class burlap.behavior.stochasticgame.agents.naiveq.SGNaiveQLAgent
getQSources() - Method in class burlap.behavior.stochasticgame.agents.maql.MultiAgentQLearning
getQSources() - Method in class burlap.behavior.stochasticgame.mavaluefunction.MAValueFunctionPlanner
getQSources() - Method in interface burlap.behavior.stochasticgame.mavaluefunction.MultiAgentQSourceProvider: Returns an object that can provide Q-value sources for each agent.
getQValueFor(State, JointAction) - Method in class burlap.behavior.stochasticgame.mavaluefunction.MAValueFunctionPlanner.BackupBasedQSource
getQValueFor(State, JointAction) - Method in interface burlap.behavior.stochasticgame.mavaluefunction.QSourceForSingleAgent: Returns a Q-value (represented with a JAQValue object) stored for the given state and joint action.
getQValueFor(State, JointAction) - Method in class burlap.behavior.stochasticgame.mavaluefunction.QSourceForSingleAgent.HashBackedQSource
getRandomGenerator() - Method in class burlap.behavior.singleagent.Policy.RandomPolicy: Returns the random generator used for action selection.
getRandomInitialState(GridWorldDomain, Domain) - Static method in class burlap.domain.singleagent.gridworld.macro.MacroCellGridWorld: Returns a random initial state in a world with no location objects.
getRandomObject() - Method in class burlap.domain.singleagent.mountaincar.MCRandomStateGenerator: Returns the random object used for generating states
getReachableHashedStates(State, SADomain, StateHashFactory) - Static method in class burlap.behavior.singleagent.auxiliary.StateReachability: Returns the set of State objects that are reachable from a source state.
getReachableHashedStates(State, SADomain, StateHashFactory, TerminalFunction) - Static method in class burlap.behavior.singleagent.auxiliary.StateReachability: Returns the set of State objects that are reachable from a source state.
getReachableStates(State, SADomain, StateHashFactory) - Static method in class burlap.behavior.singleagent.auxiliary.StateReachability: Returns the list of State objects that are reachable from a source state.
getReachableStates(State, SADomain, StateHashFactory, TerminalFunction) - Static method in class burlap.behavior.singleagent.auxiliary.StateReachability: Returns the list of State objects that are reachable from a source state.
getRealVal() - Method in class burlap.oomdp.core.Value: Returns the real-valued double value of this Value object
getRealVal() - Method in class burlap.oomdp.core.values.DiscreteValue
getRealVal() - Method in class burlap.oomdp.core.values.DoubleArrayValue
getRealVal() - Method in class burlap.oomdp.core.values.IntArrayValue
getRealVal() - Method in class burlap.oomdp.core.values.IntValue
getRealVal() - Method in class burlap.oomdp.core.values.MultiTargetRelationalValue
getRealVal() - Method in class burlap.oomdp.core.values.RealValue
getRealVal() - Method in class burlap.oomdp.core.values.RelationalValue
getRealVal() - Method in class burlap.oomdp.core.values.StringValue
getRealValForAttribute(String) - Method in class burlap.oomdp.core.ObjectInstance: Returns the double value assignment for the real-valued attribute named attName.
getRecordedEpisodes() - Method in class burlap.oomdp.singleagent.explorer.VisualExplorer: Returns the list of episodes recorded by a user.
getRegisteredAgents() - Method in class burlap.oomdp.stochasticgames.World: Returns the list of agents participating in this world.
getRenderLayer(Domain, int[][]) - Static method in class burlap.domain.singleagent.gridworld.GridWorldVisualizer: Deprecated.
getRenderLayer(int[][]) - Static method in class burlap.domain.singleagent.gridworld.GridWorldVisualizer: Returns state render layer for a gird world domain with the provided wall map.
getRenderStyle() - Method in class burlap.behavior.singleagent.auxiliary.valuefunctionvis.common.PolicyGlyphPainter2D: Returns the rendering style
getRepatedGameActionModel() - Static method in class burlap.domain.stochasticgames.normalform.SingleStageNormalFormGame: Returns a repeated game joint action model.
getRepublicanObjective(double[][]) - Static method in class burlap.behavior.stochasticgame.solvers.CorrelatedEquilibriumSolver: Returns the republican/libertarian objective for the given player's payoffs that are to be maximized.
getResetSpecialAction() - Method in class burlap.oomdp.singleagent.explorer.VisualExplorer: Returns a special action that causes the state to reset to the initial state.
getResetSpecialAction() - Method in class burlap.oomdp.stochasticgames.explorers.SGVisualExplorer: Returns the reset action being used when the reset key ` is pressed
getReward(int) - Method in class burlap.behavior.singleagent.EpisodeAnalysis: Returns the reward received at timestep t.
getRewardForAgent(int, String) - Method in class burlap.behavior.stochasticgame.GameAnalysis: Returns the reward received for the agent with the given name at the given step.
getRewardForTransitionsTo(int, int) - Method in class burlap.domain.singleagent.gridworld.GridWorldRewardFunction: Returns the reward this reward function will return when the agent transitions to position x, y.
getRewardFunction() - Method in class burlap.oomdp.singleagent.explorer.TerminalExplorer
getRewardFunction() - Method in class burlap.oomdp.stochasticgames.explorers.SGTerminalExplorer
getRewardFunction() - Method in class burlap.oomdp.stochasticgames.explorers.SGVisualExplorer
getRewardMatrix() - Method in class burlap.domain.singleagent.gridworld.GridWorldRewardFunction: Returns the reward matrix this reward function uses.
getRewardModel() - Method in class burlap.oomdp.stochasticgames.World: Returns the JointReward function used in this world.
getRf() - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.MLIRLRequest
getRF() - Method in class burlap.behavior.singleagent.planning.OOMDPPlanner: Returns the RewardFunction this planner uses.
getRf() - Method in class burlap.behavior.singleagent.planning.OOMDPPlanner
getRfDim() - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.diffvinit.LinearDiffRFVInit
getRfFvGen() - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.diffvinit.LinearDiffRFVInit
getRLGlueAction(int) - Method in class burlap.behavior.singleagent.interfaces.rlglue.RLGlueWrappedDomainGenerator: Returns the corresponding RLGlue action for the given action id.
getRoot() - Method in class burlap.behavior.singleagent.planning.stochastic.montecarlo.uct.UCT: Returns the root node of the UCT tree.
getRowPlayersStrategy(double[][]) - Static method in class burlap.behavior.stochasticgame.solvers.MinMaxSolver: Computes the minmax strategy for the row player of the given payoff matrix.
getS() - Method in class burlap.behavior.singleagent.learning.actorcritic.CritiqueResult: Returns the source state of this behavior.
getSamples() - Method in class burlap.behavior.singleagent.planning.vfa.fittedvi.FittedVI: Returns the state samples to which the value function will be fit.
getSelectionActions() - Method in class burlap.behavior.singleagent.Policy.RandomPolicy: Returns of the list of actions that can be randomly selected.
getSemiWallProb() - Method in class burlap.domain.stochasticgames.gridgame.GridGame: Returns the probability that an agent can pass through a semi-wall.
getSingleAction(String) - Method in class burlap.oomdp.core.Domain: Return the stochastic game action with the given name.
getSingleAction(String) - Method in class burlap.oomdp.singleagent.SADomain
getSingleAction(String) - Method in class burlap.oomdp.stochasticgames.SGDomain
getSingleActions() - Method in class burlap.oomdp.core.Domain: Returns a list of the stochastic game actions that that can be taken by individual agents in this domain.
getSingleActions() - Method in class burlap.oomdp.singleagent.SADomain
getSingleActions() - Method in class burlap.oomdp.stochasticgames.SGDomain
getSoftTieRenderStyleDelta() - Method in class burlap.behavior.singleagent.auxiliary.valuefunctionvis.common.PolicyGlyphPainter2D: Returns the soft difference between max actions to determine ties when the MAXACTIONSOFSOFTTIE render style is used.
getSourceDomainState(State) - Method in class burlap.domain.singleagent.tabularized.TabulatedDomainWrapper: Returns the source domain state associated with the tabularized state
getSpp() - Method in class burlap.behavior.singleagent.auxiliary.valuefunctionvis.PolicyRenderLayer: Returns the state-wise policy painter
getSpp() - Method in class burlap.behavior.singleagent.auxiliary.valuefunctionvis.ValueFunctionVisualizerGUI: Returns the state-wise policy painter
getSprime() - Method in class burlap.behavior.singleagent.learning.actorcritic.CritiqueResult: Returns the resulting state of this behavior.
getStackBottom(State, ObjectInstance) - Method in class burlap.domain.singleagent.blocksworld.BlocksWorldVisualizer.BlockPainter
getStagHunt() - Static method in class burlap.domain.stochasticgames.normalform.SingleStageNormalFormGame: Returns an instance of Stag Hunt, which is defined by:
(2,2); (0,1)
(1,0); (1,1)
getStandardGridGameAgentType(Domain) - Static method in class burlap.domain.stochasticgames.gridgame.GridGame: Creates and returns a standard AgentType for grid games.
getStartStateGenerator() - Method in class burlap.behavior.singleagent.learnbydemo.apprenticeship.ApprenticeshipLearningRequest
getState(int) - Method in class burlap.behavior.singleagent.EpisodeAnalysis: Returns the state observed at time step t.
getState(int) - Method in class burlap.behavior.stochasticgame.GameAnalysis: Returns the state stored at time step t where t=0 refers to the initial state
getState(Domain, int) - Static method in class burlap.domain.singleagent.graphdefined.GraphDefinedDomain: Returns a new state in which the agent is in the specified source node number.
getState(Domain, double, double) - Method in class burlap.domain.singleagent.mountaincar.MountainCar: Returns a state with the agent in the specified position at the specified velocity.
getState(SGDomain) - Static method in class burlap.domain.stochasticgames.normalform.SingleStageNormalFormGame: Returns a state object for a domain object generated by a SingleStageNormalFormGame object.
getStateActionNode(StateHashTuple, GroundedAction) - Method in class burlap.behavior.singleagent.learning.modellearning.models.TabularModel: Returns the TabularModel.StateActionNode object associated with the given hashed state and action.
getStateActionValues(State, List<GroundedAction>) - Method in class burlap.behavior.singleagent.vfa.common.LinearFVVFA
getStateActionValues(State, List<GroundedAction>) - Method in class burlap.behavior.singleagent.vfa.common.LinearVFA
getStateActionValues(State, List<GroundedAction>) - Method in interface burlap.behavior.singleagent.vfa.ValueFunctionApproximation: Returns a state-value (e.g., Q-value) approximation for the query state.
getStateDescription() - Method in class burlap.oomdp.core.State: Returns a string representation of this state using only observable object instances.
getStateFeatures(State) - Method in class burlap.behavior.singleagent.vfa.cmac.CMACFeatureDatabase
getStateFeatures(State) - Method in class burlap.behavior.singleagent.vfa.cmac.FVCMACFeatureDatabase
getStateFeatures(State) - Method in class burlap.behavior.singleagent.vfa.common.FVToFeatureDatabase
getStateFeatures(State) - Method in interface burlap.behavior.singleagent.vfa.FeatureDatabase: Returns non-zero state features for a given state.
getStateFeatures(State) - Method in class burlap.behavior.singleagent.vfa.fourier.FourierBasis
getStateFeatures(State) - Method in class burlap.behavior.singleagent.vfa.rbf.FVRBFFeatureDatabase
getStateFeatures(State) - Method in class burlap.behavior.singleagent.vfa.rbf.RBFFeatureDatabase
getStateForEnumertionId(int) - Method in class burlap.behavior.singleagent.auxiliary.StateEnumerator: Returns the state associated with the given enumeration id.
getStateId(State) - Method in class burlap.domain.singleagent.tabularized.TabulatedDomainWrapper: Returns the state id for a state beloning to the input source domain
getStateNode(State, int) - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.DifferentiableSparseSampling: Either returns, or creates, indexes, and returns, the state node for the given state at the given height in the tree
getStateNode(StateHashTuple) - Method in class burlap.behavior.singleagent.learning.tdmethods.QLearning: Returns the QLearningStateNode object stored for the given hashed state.
getStateNode(State, int) - Method in class burlap.behavior.singleagent.planning.stochastic.sparsesampling.SparseSampling: Either returns, or creates, indexes, and returns, the state node for the given state at the given height in the tree
getStateRenderLayer(int, int) - Static method in class burlap.domain.singleagent.blockdude.BlockDudeVisualizer: Returns a StateRenderLayer for BlockDudeVisualizer.
getStateRenderLayer(int[][], MacroCellGridWorld.InMacroCellPF[], Map<String, Double>) - Static method in class burlap.domain.singleagent.gridworld.macro.MacroCellVisualizer: Returns a StateRenderLayer for the Macro-Cell GridWorld Visualizer and reward weights associated with a set of MacroCell Propositional functions.
getStateRenderLayer(LunarLanderDomain.LLPhysicsParams) - Static method in class burlap.domain.singleagent.lunarlander.LLVisualizer: Returns a StateRenderLayer a the LunarLanderDomain using the provided LunarLanderDomain.LLPhysicsParams to define the visualized movement space and rotation degrees.
getStateRenderLayer(MountainCar.MCPhysicsParams) - Static method in class burlap.domain.singleagent.mountaincar.MountainCarVisualizer: Returns a StateRenderLayer for a MountainCar Domain using the hill design/physics defined in the MountainCar.MCPhysicsParams for visualization
getStateRenderLayer() - Method in class burlap.oomdp.visualizer.Visualizer: Returns the StateRenderLayer instance for visualizing OO-MDP states.
getStates() - Method in class burlap.behavior.stochasticgame.GameAnalysis: Returns the state sequence list object
getStatesToVisualize() - Method in class burlap.behavior.singleagent.auxiliary.valuefunctionvis.PolicyRenderLayer: Returns the states that will be visualized
getStatesToVisualize() - Method in class burlap.behavior.singleagent.auxiliary.valuefunctionvis.ValueFunctionRenderLayer: Returns the states that will be visualized
getStateTile(State) - Method in class burlap.behavior.singleagent.vfa.cmac.Tiling: Returns the multi-dimensional tile from this tiling that corresponds to the given input state.
getStateValue(State) - Method in class burlap.behavior.singleagent.vfa.common.LinearFVVFA
getStateValue(State) - Method in class burlap.behavior.singleagent.vfa.common.LinearVFA
getStateValue(State) - Method in interface burlap.behavior.singleagent.vfa.ValueFunctionApproximation: Returns a state value approximation for the query state.
getStateWiseLearningRate(State) - Method in class burlap.behavior.learningrate.ExponentialDecayLR: Returns the learning rate data structure for the given state.
getStateWiseTimeIndex(State) - Method in class burlap.behavior.learningrate.SoftTimeInverseDecayLR: Returns the learning rate data structure for the given state.
getStoredEntry(T) - Method in class burlap.datastructures.StochasticTree: Returns the pointer to the stored entry in this tree for the given query element.
getStrategyProfile(SingleStageNormalFormGame.ActionNameMap[], String...) - Static method in class burlap.domain.stochasticgames.normalform.SingleStageNormalFormGame: Returns a hashable strategy profile object for a strategy profile specified by action names
getStringVal() - Method in class burlap.oomdp.core.Value: Returns the string value of this Value object
getStringVal() - Method in class burlap.oomdp.core.values.DiscreteValue
getStringVal() - Method in class burlap.oomdp.core.values.DoubleArrayValue
getStringVal() - Method in class burlap.oomdp.core.values.IntArrayValue
getStringVal() - Method in class burlap.oomdp.core.values.IntValue
getStringVal() - Method in class burlap.oomdp.core.values.MultiTargetRelationalValue
getStringVal() - Method in class burlap.oomdp.core.values.RealValue
getStringVal() - Method in class burlap.oomdp.core.values.RelationalValue
getStringVal() - Method in class burlap.oomdp.core.values.StringValue
getStringValForAttribute(String) - Method in class burlap.oomdp.core.ObjectInstance: Returns the string value representation for the attribute named attName.
getSvp() - Method in class burlap.behavior.singleagent.auxiliary.valuefunctionvis.ValueFunctionRenderLayer: Returns the State-wise value function painter
getSvp() - Method in class burlap.behavior.singleagent.auxiliary.valuefunctionvis.ValueFunctionVisualizerGUI: Returns the State-wise value function painter
getTabularizedState(State) - Method in class burlap.domain.singleagent.tabularized.TabulatedDomainWrapper: Returns a tabularized state for a source domain state
getTemperature() - Method in class burlap.datastructures.BoltzmannDistribution: Returns the temperature parameter
getTerminalFunction() - Method in class burlap.oomdp.singleagent.explorer.TerminalExplorer
getTerminalFunction() - Method in class burlap.oomdp.singleagent.explorer.VisualExplorer
getTerminalFunction() - Method in class burlap.oomdp.stochasticgames.explorers.SGTerminalExplorer
getTerminalFunction() - Method in class burlap.oomdp.stochasticgames.explorers.SGVisualExplorer
getTerminalState() - Method in class burlap.behavior.singleagent.interfaces.rlglue.RLGlueWrappedDomainGenerator: Returns a terminal state.
getTerminalStates() - Method in class burlap.domain.singleagent.graphdefined.GraphTF
getTerminiationStates() - Method in class burlap.behavior.singleagent.options.DeterminisitcTerminationOption: Returns the object defining the termination states.
getTf() - Method in class burlap.behavior.singleagent.planning.deterministic.TFGoalCondition: Returns the TerminalFunction used to specify the goal condition.
getTF() - Method in class burlap.behavior.singleagent.planning.OOMDPPlanner: Returns the TerminalFunction this planner uses.
getTf() - Method in class burlap.behavior.singleagent.planning.OOMDPPlanner
getTF() - Method in class burlap.oomdp.stochasticgames.World: Returns the TerminalFunction used in this world.
getTHistory() - Method in class burlap.behavior.singleagent.learnbydemo.apprenticeship.ApprenticeshipLearningRequest
getThrustValue() - Method in class burlap.domain.singleagent.lunarlander.LunarLanderDomain.ActionThrust
getTime() - Method in class burlap.debugtools.MyTimer: Returns the elapsed time in seconds since the last start-stop calls.
getTotalTime() - Method in class burlap.debugtools.MyTimer: Returns the total time in seconds recorded over all start-stop calls.
getTrackingRewardFunction() - Method in class burlap.oomdp.singleagent.explorer.VisualExplorer
getTransitionDynamics() - Method in class burlap.domain.singleagent.graphdefined.GraphDefinedDomain.GraphAction
getTransitionProbabilities(State, GroundedAction) - Method in class burlap.behavior.singleagent.learning.modellearning.Model: Returns this model's transition probabilities for the given source state and action
getTransitionProbabilities(State, GroundedAction) - Method in class burlap.behavior.singleagent.learning.modellearning.models.TabularModel
getTransitions(State, String[]) - Method in class burlap.behavior.singleagent.learning.modellearning.ModeledDomainGenerator.ModeledAction
getTransitions(State, String[]) - Method in class burlap.behavior.singleagent.learning.modellearning.ModeledDomainGenerator.RMaxStateAction
getTransitions(State, String[]) - Method in class burlap.behavior.singleagent.options.Option
getTransitions(State, String[]) - Method in class burlap.domain.singleagent.blockdude.BlockDude.MoveAction
getTransitions(State, String[]) - Method in class burlap.domain.singleagent.blockdude.BlockDude.MoveUpAction
getTransitions(State, String[]) - Method in class burlap.domain.singleagent.blockdude.BlockDude.PickupAction
getTransitions(State, String[]) - Method in class burlap.domain.singleagent.blockdude.BlockDude.PutdownAction
getTransitions(State, String[]) - Method in class burlap.domain.singleagent.blocksworld.BlocksWorld.StackAction
getTransitions(State, String[]) - Method in class burlap.domain.singleagent.blocksworld.BlocksWorld.UnstackAction
getTransitions(State, String[]) - Method in class burlap.domain.singleagent.cartpole.CartPoleDomain.MovementAction
getTransitions(State, String[]) - Method in class burlap.domain.singleagent.cartpole.InvertedPendulum.ForceAction
getTransitions(State, String[]) - Method in class burlap.domain.singleagent.frostbite.FrostbiteDomain.ActionIdle
getTransitions(State, String[]) - Method in class burlap.domain.singleagent.frostbite.FrostbiteDomain.MovementAction
getTransitions(State, String[]) - Method in class burlap.domain.singleagent.graphdefined.GraphDefinedDomain.GraphAction
getTransitions(State, String[]) - Method in class burlap.domain.singleagent.gridworld.GridWorldDomain.MovementAction
getTransitions(State, String[]) - Method in class burlap.domain.singleagent.lunarlander.LunarLanderDomain.ActionIdle
getTransitions(State, String[]) - Method in class burlap.domain.singleagent.lunarlander.LunarLanderDomain.ActionThrust
getTransitions(State, String[]) - Method in class burlap.domain.singleagent.lunarlander.LunarLanderDomain.ActionTurn
getTransitions(State, String[]) - Method in class burlap.domain.singleagent.tabularized.TabulatedDomainWrapper.ActionWrapper
getTransitions(State, String) - Method in class burlap.oomdp.singleagent.Action: Returns the transition probabilities for applying this action in the given state with the given set of parameters.
getTransitions(State, String[]) - Method in class burlap.oomdp.singleagent.Action: Returns the transition probabilities for applying this action in the given state with the given set of parameters.
getTransitions(State, String[]) - Method in class burlap.oomdp.singleagent.common.NullAction
getTrueClassName() - Method in class burlap.oomdp.core.ObjectInstance: Returns the name of this object instance's object class
getTurkeyInitialState(Domain) - Static method in class burlap.domain.stochasticgames.gridgame.GridGame
getUninitializedState(Domain, int) - Static method in class burlap.domain.singleagent.blockdude.BlockDude: Returns an uninitialized state that contains the specified number of block objects.
getUnmodeledActionsForState(State) - Method in class burlap.behavior.singleagent.learning.modellearning.Model: Returns a list specifying the actions for which the transition dynamics are not yet "known."
getUnmodeledActionsForState(State) - Method in class burlap.behavior.singleagent.learning.modellearning.models.TabularModel
getUseSemiDeep() - Method in class burlap.domain.singleagent.blockdude.BlockDude: Returns whether generated domain's actions use semi-deep state copies or full deep copies..
getUsingMaxMargin() - Method in class burlap.behavior.singleagent.learnbydemo.apprenticeship.ApprenticeshipLearningRequest
getUtilitarianObjective(double[][], double[][]) - Static method in class burlap.behavior.stochasticgame.solvers.CorrelatedEquilibriumSolver: Returns the utilitarian objective for the given payoffs for the row and column player.
getV(StateHashTuple) - Method in class burlap.behavior.singleagent.learning.actorcritic.critics.TDLambda: Returns the TDLambda.VValue object (storing the value) for a given hashed stated.
getV(StateHashTuple, int) - Method in class burlap.behavior.singleagent.learning.actorcritic.critics.TimeIndexedTDLambda: Returns the TDLambda.VValue object (storing the value) for a given hashed stated at the specified time/depth.
getValue(StateHashTuple) - Method in class burlap.behavior.stochasticgame.mavaluefunction.MAValueFunctionPlanner.BackupBasedQSource: Returns the stored state value for hashed state sh, or creates an entry with an initial value corresponding to the MAValueFunctionPlanner instance's value function initialization object and returns that value if the the quried state has never previously been indexed.
getValueForAttribute(String) - Method in class burlap.oomdp.core.ObjectInstance: Returns the Value object assignment for the attribute named attName
getValueFunctionInitialization() - Method in class burlap.behavior.singleagent.planning.ValueFunctionPlanner: Returns the value initialization function used.
getValueGradient(State) - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.DifferentiableVFPlanner: Returns the value function gradient for the given State
getValueIterationPlanner() - Method in class burlap.behavior.singleagent.learning.modellearning.modelplanners.VIModelPlanner: Returns the value iteration object used for planning whenever the model updates.
getValues() - Method in class burlap.oomdp.core.ObjectInstance: Returns the list of value object assignments to all of this object instance's attributes.
getVGradient(State) - Method in interface burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.diffvinit.DifferentiableVInit: Returns the value function gradient.
getVGradient(State) - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.diffvinit.LinearDiffRFVInit
getVGradient(State) - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.diffvinit.LinearStateDiffVF
getVGradient(State) - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.diffvinit.VanillaDiffVinit
getVInit() - Method in class burlap.behavior.singleagent.planning.vfa.fittedvi.FittedVI: Returns the value function initialization used at the start of planning.
getVinitDim() - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.diffvinit.LinearDiffRFVInit
getVinitFvGen() - Method in class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.diffvinit.LinearDiffRFVInit
getVisualizer(int, int) - Static method in class burlap.domain.singleagent.blockdude.BlockDudeVisualizer: Returns a Visualizer for BlockDude.
getVisualizer() - Static method in class burlap.domain.singleagent.blocksworld.BlocksWorldVisualizer: Returns a 2D Visualizer canvas object to visualize BlocksWorld states.
getVisualizer(int) - Static method in class burlap.domain.singleagent.blocksworld.BlocksWorldVisualizer: Returns a 2D Visualizer canvas object to visualize BlocksWorld states where the name of the block is rendered at the provided font point size.
getVisualizer(FrostbiteDomain) - Static method in class burlap.domain.singleagent.frostbite.FrostbiteVisualizer: Returns a visualizer for a lunar lander domain.
getVisualizer(Domain, int[][]) - Static method in class burlap.domain.singleagent.gridworld.GridWorldVisualizer: Deprecated.
getVisualizer(int[][]) - Static method in class burlap.domain.singleagent.gridworld.GridWorldVisualizer: Returns visualizer for a grid world domain with the provided wall map.
getVisualizer(int[][], MacroCellGridWorld.InMacroCellPF[], Map<String, Double>) - Static method in class burlap.domain.singleagent.gridworld.macro.MacroCellVisualizer: Returns a Visualizer for the Macro-Cell GridWorld Visualizer and reward weights associated with a set of MacroCell Propositional functions.
getVisualizer(LunarLanderDomain) - Static method in class burlap.domain.singleagent.lunarlander.LLVisualizer: Returns a Visualizer for a LunarLanderDomain using the generator's current version of the physics parameters for defining the visualized movement space size and rotation degrees.
getVisualizer(LunarLanderDomain.LLPhysicsParams) - Static method in class burlap.domain.singleagent.lunarlander.LLVisualizer: Returns a Visualizer a the LunarLanderDomain using the provided LunarLanderDomain.LLPhysicsParams to define the visualized movement space and rotation degrees.
getVisualizer(MountainCar) - Static method in class burlap.domain.singleagent.mountaincar.MountainCarVisualizer: Returns a Visualizer for a MountainCar Domain using the hill design/physics defined in the DomainGenerator for visualization
getVisualizer(MountainCar.MCPhysicsParams) - Static method in class burlap.domain.singleagent.mountaincar.MountainCarVisualizer: Returns a Visualizer for a MountainCar Domain using the hill design/physics defined in the MountainCar.MCPhysicsParams for visualization
getVisualizer(int, int) - Static method in class burlap.domain.stochasticgames.gridgame.GGVisualizer: Generates a visualizer for a grid game
getVmax() - Method in class burlap.domain.singleagent.lunarlander.LunarLanderDomain: Returns the maximum velocity of the agent (the agent cannot move faster than this value).
getVmax() - Method in class burlap.domain.singleagent.lunarlander.LunarLanderDomain.LLPhysicsParams
getVmax() - Method in class burlap.domain.singleagent.mountaincar.MCRandomStateGenerator: Returns the maximum velocity that a generated state can have.
getVmin() - Method in class burlap.domain.singleagent.mountaincar.MCRandomStateGenerator: Returns the minimum velocity that a generated state can have.
getVValue(State) - Method in class burlap.behavior.singleagent.auxiliary.valuefunctionvis.ValueFunctionRenderLayer: Returns the value for a state
getWeightGradient(ApproximationResult) - Method in class burlap.behavior.singleagent.vfa.common.LinearFVVFA
getWeightGradient(ApproximationResult) - Method in class burlap.behavior.singleagent.vfa.common.LinearVFA
getWeightGradient(ApproximationResult) - Method in interface burlap.behavior.singleagent.vfa.ValueFunctionApproximation: Returns the function weight gradient of the given approximation result.
getWidth() - Method in class burlap.domain.singleagent.gridworld.GridWorldDomain: Returns this grid world's width
getWinningAgentMovements(Map<Integer, List<Integer>>) - Method in class burlap.domain.stochasticgames.gridgame.GridGameStandardMechanics: Takes as input the set of collisions and randomly selects a winner
getX2ndDeriv(double, double, double, double, double, double, CartPoleDomain.CPPhysicsParams) - Static method in class burlap.domain.singleagent.cartpole.CartPoleDomain: Returns the second order x position derivative for the corrected model.
getXmax() - Method in class burlap.domain.singleagent.lunarlander.LunarLanderDomain: Returns the maximum x position of the lander (the agent cannot cross this boundary)
getXmax() - Method in class burlap.domain.singleagent.lunarlander.LunarLanderDomain.LLPhysicsParams
getXmax() - Method in class burlap.domain.singleagent.mountaincar.MCRandomStateGenerator: Returns the maximum x-value that a generated state can have.
getXmin() - Method in class burlap.domain.singleagent.lunarlander.LunarLanderDomain: Returns the minimum x position of the lander (the agent cannot cross this boundary)
getXmin() - Method in class burlap.domain.singleagent.lunarlander.LunarLanderDomain.LLPhysicsParams
getXmin() - Method in class burlap.domain.singleagent.mountaincar.MCRandomStateGenerator: Returns the minimum x-value that a generated state can have.
getYAMLPrepared(State) - Method in class burlap.oomdp.auxiliary.common.StateYAMLParser: Returns the data structure of a state that is passed to YAML.
getYmax() - Method in class burlap.domain.singleagent.lunarlander.LunarLanderDomain: Returns the maximum y position of the lander (the agent cannot cross this boundary)
getYmax() - Method in class burlap.domain.singleagent.lunarlander.LunarLanderDomain.LLPhysicsParams
getYmin() - Method in class burlap.domain.singleagent.lunarlander.LunarLanderDomain: Returns the minimum y position of the lander (the agent cannot cross this boundary)
getYmin() - Method in class burlap.domain.singleagent.lunarlander.LunarLanderDomain.LLPhysicsParams
GGVisualizer - Class in burlap.domain.stochasticgames.gridgame: A class for visualizing the grid games.
GGVisualizer() - Constructor for class burlap.domain.stochasticgames.gridgame.GGVisualizer
GoalBasedRF - Class in burlap.behavior.singleagent.learning: A reward function implementation designed around goal conditions that are specified by a StateConditionTest object.
GoalBasedRF(StateConditionTest) - Constructor for class burlap.behavior.singleagent.learning.GoalBasedRF: Initializes with transitions to goal states returning a reward of 1 and all others returning 0
GoalBasedRF(StateConditionTest, double) - Constructor for class burlap.behavior.singleagent.learning.GoalBasedRF: Initializes with transitions to goal states returning the given reward and all others returning 0.
GoalBasedRF(StateConditionTest, double, double) - Constructor for class burlap.behavior.singleagent.learning.GoalBasedRF: Initializes with transitions to goal states returning the given reward and all others returning 0.
GoalBasedRF(TerminalFunction) - Constructor for class burlap.behavior.singleagent.learning.GoalBasedRF: Initializes with transitions to goal states, indicated by the terminal function, returning a reward of 1 and all others returning 0
GoalBasedRF(TerminalFunction, double) - Constructor for class burlap.behavior.singleagent.learning.GoalBasedRF: Initializes with transitions to goal states, indicated by the terminal function, returning the given reward and all others returning 0.
GoalBasedRF(TerminalFunction, double, double) - Constructor for class burlap.behavior.singleagent.learning.GoalBasedRF: Initializes with transitions to goal states, indicated by the terminal function, returning the given reward and all others returning 0.
goalCondition - Variable in class burlap.behavior.singleagent.planning.stochastic.montecarlo.uct.UCT
goalCondition - Variable in class burlap.behavior.singleagent.planning.stochastic.rtdp.BFSRTDP: The goal condition that stops the BFS-like pass
GoalConditionTF - Class in burlap.behavior.singleagent.planning.deterministic: Creates a terminal function that indicates terminal states are any states that satisfy a goal condition where the goal condition is specified by a StateConditionTest object.
GoalConditionTF(StateConditionTest) - Constructor for class burlap.behavior.singleagent.planning.deterministic.GoalConditionTF
goalReward - Variable in class burlap.behavior.singleagent.learning.GoalBasedRF
goalReward - Variable in class burlap.domain.singleagent.frostbite.FrostbiteRF
goalReward - Variable in class burlap.domain.singleagent.lunarlander.LunarLanderRF: The reward for landing on the landing pad
gradient - Variable in class burlap.behavior.singleagent.learnbydemo.mlirl.support.QGradientTuple: The gradient for the state and action.
GradientDescentSarsaLam - Class in burlap.behavior.singleagent.learning.tdmethods.vfa: Gradient Descent SARSA(\lambda) implementation [1].
GradientDescentSarsaLam(Domain, RewardFunction, TerminalFunction, double, ValueFunctionApproximation, double, double) - Constructor for class burlap.behavior.singleagent.learning.tdmethods.vfa.GradientDescentSarsaLam: Initializes SARSA(\lambda) with 0.1 epsilon greedy policy and places no limit on the number of steps the agent can take in an episode.
GradientDescentSarsaLam(Domain, RewardFunction, TerminalFunction, double, ValueFunctionApproximation, double, int, double) - Constructor for class burlap.behavior.singleagent.learning.tdmethods.vfa.GradientDescentSarsaLam: Initializes SARSA(\lambda) with 0.1 epsilon greedy policy.
GradientDescentSarsaLam(Domain, RewardFunction, TerminalFunction, double, ValueFunctionApproximation, double, Policy, int, double) - Constructor for class burlap.behavior.singleagent.learning.tdmethods.vfa.GradientDescentSarsaLam: Initializes SARSA(\lambda) By default the agent will only save the last learning episode and a call to the GradientDescentSarsaLam.planFromState(State) method will cause the planner to use only one episode for planning; this should probably be changed to a much larger value if you plan on using this algorithm as a planning algorithm.
GradientDescentSarsaLam.EligibilityTraceVector - Class in burlap.behavior.singleagent.learning.tdmethods.vfa: An object for keeping track of the eligibility traces within an episode for each VFA weight
GradientDescentSarsaLam.EligibilityTraceVector(FunctionWeight, double) - Constructor for class burlap.behavior.singleagent.learning.tdmethods.vfa.GradientDescentSarsaLam.EligibilityTraceVector: Creates a trace for the given weight with the given eligibility value
GraphDefinedDomain - Class in burlap.domain.singleagent.graphdefined: A domain generator for generating domains that are represented as graphs.
GraphDefinedDomain() - Constructor for class burlap.domain.singleagent.graphdefined.GraphDefinedDomain: Initializes the generator.
GraphDefinedDomain(int) - Constructor for class burlap.domain.singleagent.graphdefined.GraphDefinedDomain: Initializes the generator to create a domain with the given number of state nodes in it.
GraphDefinedDomain.GraphAction - Class in burlap.domain.singleagent.graphdefined: An action class for defining actions that can be taken from state nodes.
GraphDefinedDomain.GraphAction(Domain, int, Map<Integer, Map<Integer, Set<GraphDefinedDomain.NodeTransitionProbibility>>>) - Constructor for class burlap.domain.singleagent.graphdefined.GraphDefinedDomain.GraphAction: Initializes a graph action object for the given domain and for the action of the given number.
GraphDefinedDomain.NodeTransitionProbibility - Class in burlap.domain.singleagent.graphdefined: A class for specifying transition probabilities to result node states.
GraphDefinedDomain.NodeTransitionProbibility(int, double) - Constructor for class burlap.domain.singleagent.graphdefined.GraphDefinedDomain.NodeTransitionProbibility: Initializes transition probability
GraphRF - Class in burlap.domain.singleagent.graphdefined: An abstract class for more easily defining RewardFunctions for GraphDefinedDomain Domains.
GraphRF() - Constructor for class burlap.domain.singleagent.graphdefined.GraphRF
GraphTF - Class in burlap.domain.singleagent.graphdefined: A TerminalFunction for instances of GraphDefinedDomain.
GraphTF(int...) - Constructor for class burlap.domain.singleagent.graphdefined.GraphTF: Initializes setting all states with the provide integer node ids to be terminal states
gravity - Variable in class burlap.domain.singleagent.cartpole.CartPoleDomain.CPPhysicsParams: the force of gravity; should be *positive* for the correct mechanics.
gravity - Variable in class burlap.domain.singleagent.cartpole.InvertedPendulum.IPPhysicsParams: the force of gravity; should be *positive* for the correct mechanics.
gravity - Variable in class burlap.domain.singleagent.lunarlander.LunarLanderDomain.LLPhysicsParams: The force of gravity
gravity - Variable in class burlap.domain.singleagent.mountaincar.MountainCar.MCPhysicsParams: The force of gravity
greatestHeightBelow(State, int[], int, int, int) - Static method in class burlap.domain.singleagent.blockdude.BlockDude: Returns the maximum height of the world at the provided x coordinate that is <= the value maxY.
GreedyDeterministicQPolicy - Class in burlap.behavior.singleagent.planning.commonpolicies: A greedy policy that breaks ties by choosing the first action with the maximum value.
GreedyDeterministicQPolicy() - Constructor for class burlap.behavior.singleagent.planning.commonpolicies.GreedyDeterministicQPolicy
GreedyDeterministicQPolicy(QComputablePlanner) - Constructor for class burlap.behavior.singleagent.planning.commonpolicies.GreedyDeterministicQPolicy: Initializes with a QComputablePlanner
GreedyQPolicy - Class in burlap.behavior.singleagent.planning.commonpolicies: A greedy policy that breaks ties by randomly choosing an action amongst the tied actions.
GreedyQPolicy() - Constructor for class burlap.behavior.singleagent.planning.commonpolicies.GreedyQPolicy
GreedyQPolicy(QComputablePlanner) - Constructor for class burlap.behavior.singleagent.planning.commonpolicies.GreedyQPolicy: Initializes with a QComputablePlanner
gridEntireDomainSpace(Domain, int) - Method in class burlap.behavior.singleagent.auxiliary.StateGridder: Grids an entire domain; that is each ObjectClass associated with the domain will have each of its associated Attributes gridded (each spanning the specified number of grid points).
gridEntireObjectClass(ObjectClass, int) - Method in class burlap.behavior.singleagent.auxiliary.StateGridder: Grids an entire Object class object with each of its associated attributes having the grid span their whole domain with the same number of grid points.
GridGame - Class in burlap.domain.stochasticgames.gridgame: The GridGame domain is much like the GridWorld domain, except for arbitrarily many agents in a stochastic game.
GridGame() - Constructor for class burlap.domain.stochasticgames.gridgame.GridGame
GridGame.GGJointRewardFunction - Class in burlap.domain.stochasticgames.gridgame: Specifies goal rewards and default rewards for agents.
GridGame.GGJointRewardFunction(Domain) - Constructor for class burlap.domain.stochasticgames.gridgame.GridGame.GGJointRewardFunction: Initializes for a given domain.
GridGame.GGJointRewardFunction(Domain, double, double, boolean) - Constructor for class burlap.domain.stochasticgames.gridgame.GridGame.GGJointRewardFunction: Initializes for a given domain, step cost reward and goal reward.
GridGame.GGJointRewardFunction(Domain, double, double, double, boolean) - Constructor for class burlap.domain.stochasticgames.gridgame.GridGame.GGJointRewardFunction: Initializes for a given domain, step cost reward, personal goal reward, and universal goal reward.
GridGame.GGJointRewardFunction(Domain, double, double, boolean, Map<Integer, Double>) - Constructor for class burlap.domain.stochasticgames.gridgame.GridGame.GGJointRewardFunction: Initializes for a given domain, step cost reward, universal goal reward, and unique personal goal reward for each player.
GridGame.GGTerminalFunction - Class in burlap.domain.stochasticgames.gridgame: Causes termination when any agent reaches a personal or universal goal location.
GridGame.GGTerminalFunction(Domain) - Constructor for class burlap.domain.stochasticgames.gridgame.GridGame.GGTerminalFunction: Initializes for the given domain
GridGameStandardMechanics - Class in burlap.domain.stochasticgames.gridgame: This class defines the standard transition dynamics for a grid game.
GridGameStandardMechanics(Domain) - Constructor for class burlap.domain.stochasticgames.gridgame.GridGameStandardMechanics: Initializes the mechanics for the given domain and sets the semi-wall pass through probability to 0.5;
GridGameStandardMechanics(Domain, double) - Constructor for class burlap.domain.stochasticgames.gridgame.GridGameStandardMechanics: Initializes the mechanics for the given domain and sets the semi-wall pass through probability to semiWallPassThroughProb.
gridInputState(State) - Method in class burlap.behavior.singleagent.auxiliary.StateGridder: Creates a grid using the input state a source reference.
GridWorldDomain - Class in burlap.domain.singleagent.gridworld: A domain generator for basic grid worlds.
GridWorldDomain(int, int) - Constructor for class burlap.domain.singleagent.gridworld.GridWorldDomain: Constructs an empty map with deterministic transitions
GridWorldDomain(int[][]) - Constructor for class burlap.domain.singleagent.gridworld.GridWorldDomain: Constructs a deterministic world based on the provided map.
GridWorldDomain.AtLocationPF - Class in burlap.domain.singleagent.gridworld: Propositional function for determining if the agent is at the same position as a given location object
GridWorldDomain.AtLocationPF(String, Domain, String[]) - Constructor for class burlap.domain.singleagent.gridworld.GridWorldDomain.AtLocationPF: Initializes with given name domain and parameter object class types
GridWorldDomain.MovementAction - Class in burlap.domain.singleagent.gridworld: Action class for movement actions in grid world.
GridWorldDomain.MovementAction(String, Domain, double[], int[][]) - Constructor for class burlap.domain.singleagent.gridworld.GridWorldDomain.MovementAction: Initializes for the given name, domain and actually direction probabilities the agent will go
GridWorldDomain.WallToPF - Class in burlap.domain.singleagent.gridworld: Propositional function for indicating if a wall is in a given position relative to the agent position
GridWorldDomain.WallToPF(String, Domain, String[], int) - Constructor for class burlap.domain.singleagent.gridworld.GridWorldDomain.WallToPF: Initializes the function.
GridWorldRewardFunction - Class in burlap.domain.singleagent.gridworld: This class is used for defining reward functions in grid worlds that are a function of cell of the world to which the agent transitions.
GridWorldRewardFunction(int, int, double) - Constructor for class burlap.domain.singleagent.gridworld.GridWorldRewardFunction: Initializes the reward function for a grid world of size width and height and initializes the reward values everywhere to initializingReward.
GridWorldRewardFunction(int, int) - Constructor for class burlap.domain.singleagent.gridworld.GridWorldRewardFunction: Initializes the reward function for a grid world of size width and height and initializes the reward values everywhere to 0.
GridWorldRewardFunction(Domain, double) - Constructor for class burlap.domain.singleagent.gridworld.GridWorldRewardFunction: Initializes the reward function for a grid world with a size defined by the attributes of the domain object to initializingReward.
GridWorldRewardFunction(Domain) - Constructor for class burlap.domain.singleagent.gridworld.GridWorldRewardFunction: Initializes the reward function for a grid world with a size defined by the attributes of the domain object to 0.
GridWorldStateParser - Class in burlap.domain.singleagent.gridworld: Simplified state parser for grid world states.
GridWorldStateParser(int, int) - Constructor for class burlap.domain.singleagent.gridworld.GridWorldStateParser
GridWorldStateParser(Domain) - Constructor for class burlap.domain.singleagent.gridworld.GridWorldStateParser
GridWorldTerminalFunction - Class in burlap.domain.singleagent.gridworld: This class is used for setting a terminal function for GridWorlds that is based on the location of the agent in the world.
GridWorldTerminalFunction() - Constructor for class burlap.domain.singleagent.gridworld.GridWorldTerminalFunction: Initializes without any terminal positions specified.
GridWorldTerminalFunction(int, int) - Constructor for class burlap.domain.singleagent.gridworld.GridWorldTerminalFunction: Initializes with a terminal position at the specified agent x and y locaiton.
GridWorldTerminalFunction(GridWorldTerminalFunction.IntPair...) - Constructor for class burlap.domain.singleagent.gridworld.GridWorldTerminalFunction: Initializes with a list of terminal positions specified by a sequence of GridWorldTerminalFunction.IntPair objects.
GridWorldTerminalFunction.IntPair - Class in burlap.domain.singleagent.gridworld: A pair class for two ints.
GridWorldTerminalFunction.IntPair(int, int) - Constructor for class burlap.domain.singleagent.gridworld.GridWorldTerminalFunction.IntPair
GridWorldVisualizer - Class in burlap.domain.singleagent.gridworld: Returns a visualizer for grid worlds in which walls are rendered as black squares or black lines, the agent is a gray circle and the location objects are colored squares.
GridWorldVisualizer() - Constructor for class burlap.domain.singleagent.gridworld.GridWorldVisualizer
GridWorldVisualizer.CellPainter - Class in burlap.domain.singleagent.gridworld: A painter for a grid world cell which will fill the cell with a given color and where the cell position is indicated by the x and y attribute for the mapped object instance
GridWorldVisualizer.CellPainter(Color, int[][]) - Constructor for class burlap.domain.singleagent.gridworld.GridWorldVisualizer.CellPainter: Initializes painter for a rectangle shape cell
GridWorldVisualizer.CellPainter(int, Color, int[][]) - Constructor for class burlap.domain.singleagent.gridworld.GridWorldVisualizer.CellPainter: Initializes painter with filling the cell with the given shape
GridWorldVisualizer.LocationPainter - Class in burlap.domain.singleagent.gridworld: A painter for location objects which will fill the cell with a given color and where the cell position is indicated by the x and y attribute for the mapped object instance
GridWorldVisualizer.LocationPainter(int[][]) - Constructor for class burlap.domain.singleagent.gridworld.GridWorldVisualizer.LocationPainter: Initializes painter
GridWorldVisualizer.MapPainter - Class in burlap.domain.singleagent.gridworld: A static painter class for rendering the walls of the grid world as black squares or black lines for 1D walls.
GridWorldVisualizer.MapPainter(int[][]) - Constructor for class burlap.domain.singleagent.gridworld.GridWorldVisualizer.MapPainter: Initializes for the domain and wall map
GrimTrigger - Class in burlap.behavior.stochasticgame.agents.twoplayer.repeatedsinglestage: A class for an agent that plays grim trigger.
GrimTrigger(SGDomain, SingleAction, SingleAction) - Constructor for class burlap.behavior.stochasticgame.agents.twoplayer.repeatedsinglestage.GrimTrigger: Initializes with the specified cooperate and defect actions for both players.
GrimTrigger(SGDomain, SingleAction, SingleAction, SingleAction) - Constructor for class burlap.behavior.stochasticgame.agents.twoplayer.repeatedsinglestage.GrimTrigger: Initializes with differently specified cooperate and defect actions for both players.
grimTrigger - Variable in class burlap.behavior.stochasticgame.agents.twoplayer.repeatedsinglestage.GrimTrigger: Whether this agent will play its defect action or not.
GrimTrigger.GrimTriggerAgentFactory - Class in burlap.behavior.stochasticgame.agents.twoplayer.repeatedsinglestage: An agent factory for GrimTrigger
GrimTrigger.GrimTriggerAgentFactory(SGDomain, SingleAction, SingleAction) - Constructor for class burlap.behavior.stochasticgame.agents.twoplayer.repeatedsinglestage.GrimTrigger.GrimTriggerAgentFactory: Initializes with the specified cooperate and defect actions for both players.
GrimTrigger.GrimTriggerAgentFactory(SGDomain, SingleAction, SingleAction, SingleAction) - Constructor for class burlap.behavior.stochasticgame.agents.twoplayer.repeatedsinglestage.GrimTrigger.GrimTriggerAgentFactory: Initializes with differently specified cooperate and defect actions for both players.
GroundedAction - Class in burlap.oomdp.singleagent: A grounded action contains a reference to an action and the names of object instances that are bound to the Action's parameters.
GroundedAction(Action, String[]) - Constructor for class burlap.oomdp.singleagent.GroundedAction: Initializes the GroundedAction with the given Action reference and action parameters.
GroundedAction(Action, String) - Constructor for class burlap.oomdp.singleagent.GroundedAction: Initializes the GroundedAction with the given Action reference and action parameters.
GroundedProp - Class in burlap.oomdp.core: Propositional functions are defined to be evaluated on object parameters and this class provides a definition for a grounded propositional function; that is, it specifies specific object parameters on which the propositional function should be evaluated.
GroundedProp(PropositionalFunction, String[]) - Constructor for class burlap.oomdp.core.GroundedProp: Initializes a grounded propositional function
GroundedSingleAction - Class in burlap.oomdp.stochasticgames: Provides a grounded version of a SingleAction.
GroundedSingleAction(String, SingleAction, String[]) - Constructor for class burlap.oomdp.stochasticgames.GroundedSingleAction: Initializes this object with the name of the acting agent, the SingleAction reference, and the parameters used.
GroundedSingleAction(String, SingleAction, String) - Constructor for class burlap.oomdp.stochasticgames.GroundedSingleAction: Initializes this object with the name of the acting agent, the SingleAction reference, and the parameters used.
gsa - Variable in class burlap.behavior.stochasticgame.agents.interfacing.singleagent.SingleAgentInterface.MutableGroundedSingleAction

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