- dataset - Variable in class burlap.behavior.singleagent.learning.lspi.LSPI
-
The SARS dataset on which LSPI is performed
- dataset - Variable in class burlap.behavior.singleagent.learning.lspi.SARSData
-
- datasets - Variable in class burlap.behavior.stochasticgame.auxiliary.performance.MultiAgentPerformancePlotter.DatasetsAndTrials
-
The series datasets for this agent
- DDPlannerPolicy - Class in burlap.behavior.singleagent.planning.deterministic
-
This is a dynamic deterministic planner policy, which means
if the source deterministic planner has not already computed
and cached the plan for a query state, then this policy
will first compute a plan using the planner and then return the
answer
- DDPlannerPolicy() - Constructor for class burlap.behavior.singleagent.planning.deterministic.DDPlannerPolicy
-
- DDPlannerPolicy(DeterministicPlanner) - Constructor for class burlap.behavior.singleagent.planning.deterministic.DDPlannerPolicy
-
Initializes with the deterministic planner
- debugCode - Variable in class burlap.behavior.singleagent.auxiliary.performance.LearningAlgorithmExperimenter
-
The debug code used for debug printing.
- debugCode - Variable in class burlap.behavior.singleagent.interfaces.rlglue.RLGlueAgentShell
-
Debug code used for printing debug information.
- debugCode - Variable in class burlap.behavior.singleagent.learnbydemo.mlirl.MLIRL
-
The debug code used for printing information to the terminal.
- debugCode - Variable in class burlap.behavior.singleagent.learnbydemo.mlirl.MultipleIntentionsMLIRL
-
The debug code used for printing information to the terminal.
- debugCode - Variable in class burlap.behavior.singleagent.planning.OOMDPPlanner
-
The debug code use for calls to
DPrint
- debugCode - Variable in class burlap.behavior.stochasticgame.auxiliary.performance.MultiAgentExperimenter
-
The debug code used for debug printing.
- debugCode - Variable in class burlap.behavior.stochasticgame.auxiliary.performance.MultiAgentPerformancePlotter
-
The debug code used for debug printing.
- debugCode - Variable in class burlap.behavior.stochasticgame.mavaluefunction.vfplanners.MAValueIteration
-
The debug code used for printing VI progress.
- debugCode - Variable in class burlap.oomdp.core.Domain
-
- debugCodeRFWeights - Static variable in class burlap.behavior.singleagent.learnbydemo.apprenticeship.ApprenticeshipLearning
-
- debugCodeScore - Static variable in class burlap.behavior.singleagent.learnbydemo.apprenticeship.ApprenticeshipLearning
-
- DebugFlags - Class in burlap.debugtools
-
A data structure for specifying debug flags that can be accessed and modified from any class
- DebugFlags() - Constructor for class burlap.debugtools.DebugFlags
-
- debugID - Static variable in class burlap.behavior.singleagent.auxiliary.StateReachability
-
The debugID used for making calls to
DPrint.
- debugId - Variable in class burlap.oomdp.stochasticgames.tournament.Tournament
-
- debugId - Variable in class burlap.oomdp.stochasticgames.World
-
- decayConstantShift - Variable in class burlap.behavior.learningrate.SoftTimeInverseDecayLR
-
The division scale offset
- decayRate - Variable in class burlap.behavior.learningrate.ExponentialDecayLR
-
The exponential base by which the learning rate is decayed
- deepCopyActionNameMapArray(SingleStageNormalFormGame.ActionNameMap[]) - Static method in class burlap.domain.stochasticgames.normalform.SingleStageNormalFormGame.ActionNameMap
-
- DEFAULT_EPSILON - Static variable in class burlap.behavior.singleagent.learnbydemo.apprenticeship.ApprenticeshipLearningRequest
-
- DEFAULT_MAXITERATIONS - Static variable in class burlap.behavior.singleagent.learnbydemo.apprenticeship.ApprenticeshipLearningRequest
-
- DEFAULT_POLICYCOUNT - Static variable in class burlap.behavior.singleagent.learnbydemo.apprenticeship.ApprenticeshipLearningRequest
-
- DEFAULT_USEMAXMARGIN - Static variable in class burlap.behavior.singleagent.learnbydemo.apprenticeship.ApprenticeshipLearningRequest
-
- DEFAULTBIMATRIXACTIONBASENAME - Static variable in class burlap.domain.stochasticgames.normalform.SingleStageNormalFormGame
-
- defaultCost(String, JointAction) - Method in class burlap.domain.stochasticgames.gridgame.GridGame.GGJointRewardFunction
-
Returns a default cost for an agent assuming the agent didn't transition to a goal state.
- DEFAULTHEIGHT - Static variable in class burlap.domain.singleagent.gridworld.macro.MacroCellGridWorld
-
- defaultMultiple - Variable in class burlap.behavior.statehashing.DiscretizingStateHashFactory
-
The default multiple to use for any continuous attributes that have not been specifically set.
- defaultQ - Variable in class burlap.behavior.stochasticgame.agents.naiveq.SGNaiveQFactory
-
The default Q-value to which Q-values will be initialized
- defaultReward - Variable in class burlap.behavior.singleagent.learning.GoalBasedRF
-
- defaultReward - Variable in class burlap.behavior.singleagent.options.LocalSubgoalRF
-
Defines the reward returned for transitions to applicable states, but not subgoal states; default -1
- defaultReward - Variable in class burlap.domain.singleagent.frostbite.FrostbiteRF
-
- defaultReward - Variable in class burlap.domain.singleagent.lunarlander.LunarLanderRF
-
The default reward received for moving through the air
- defaultTileWidth - Variable in class burlap.behavior.singleagent.interfaces.rlglue.common.RLGlueCMACSarsaLambdaFactory
-
The default tile width to use for unspecified attributes
- defaultToLowerValueAfterPlanning - Variable in class burlap.behavior.singleagent.planning.stochastic.rtdp.BoundedRTDP
-
Sets what the
ValueFunctionPlanner valueFunction reference points to (the lower bound or upperbound) once a planning rollout is complete.
- defaultWeight - Variable in class burlap.behavior.singleagent.vfa.common.LinearFVVFA
-
A default weight value for the functions weights.
- defaultWeight - Variable in class burlap.behavior.singleagent.vfa.common.LinearVFA
-
A default weight for the functions
- DEFAULTWIDTH - Static variable in class burlap.domain.singleagent.gridworld.macro.MacroCellGridWorld
-
- delay - Variable in class burlap.behavior.singleagent.auxiliary.performance.PerformancePlotter
-
the delay in milliseconds between which the charts are updated automatically
- delay - Variable in class burlap.behavior.stochasticgame.auxiliary.performance.MultiAgentPerformancePlotter
-
the delay in milliseconds between which the charts are updated automatically
- delta - Static variable in class burlap.testing.TestPlanning
-
- depth - Variable in class burlap.behavior.singleagent.planning.stochastic.montecarlo.uct.UCTStateNode
-
The depth the UCT tree
- depthMap - Variable in class burlap.behavior.singleagent.planning.deterministic.informed.astar.DynamicWeightedAStar
-
Data structure for storing the depth of explored states
- DeterminisitcTerminationOption - Class in burlap.behavior.singleagent.options
-
An option with a defined policy, initiation state set and termination state set.
- DeterminisitcTerminationOption(String, Policy, StateConditionTest, StateConditionTest) - Constructor for class burlap.behavior.singleagent.options.DeterminisitcTerminationOption
-
Initializes.
- DeterminisitcTerminationOption(String, StateConditionTestIterable, StateConditionTest, OOMDPPlanner, PlannerDerivedPolicy) - Constructor for class burlap.behavior.singleagent.options.DeterminisitcTerminationOption
-
Initializes the option by creating the policy uses some provided option.
- DeterminisitcTerminationOption(String, StateConditionTest, StateConditionTest, List<State>, OOMDPPlanner, PlannerDerivedPolicy) - Constructor for class burlap.behavior.singleagent.options.DeterminisitcTerminationOption
-
Initializes the option by creating the policy uses some provided option.
- DeterministicPlanner - Class in burlap.behavior.singleagent.planning.deterministic
-
This class extends the OOMDPlanner to provide the interface and common mechanisms for classic deterministic forward search planners.
- DeterministicPlanner() - Constructor for class burlap.behavior.singleagent.planning.deterministic.DeterministicPlanner
-
- DeterministicPlanner.PlanningFailedException - Exception in burlap.behavior.singleagent.planning.deterministic
-
Exception class for indicating that a solution failed to be found by the planning algorithm.
- DeterministicPlanner.PlanningFailedException() - Constructor for exception burlap.behavior.singleagent.planning.deterministic.DeterministicPlanner.PlanningFailedException
-
- deterministicPlannerInit(Domain, RewardFunction, TerminalFunction, StateConditionTest, StateHashFactory) - Method in class burlap.behavior.singleagent.planning.deterministic.DeterministicPlanner
-
Initializes the planner.
- deterministicTransition(State, String[]) - Method in class burlap.oomdp.singleagent.Action
-
- deterministicTransitionProbsFor(State, JointAction) - Method in class burlap.oomdp.stochasticgames.JointActionModel
-
A helper method for deterministic transition dynamics.
- DFS - Class in burlap.behavior.singleagent.planning.deterministic.uninformed.dfs
-
Implements depth-first search.
- DFS(Domain, StateConditionTest, StateHashFactory) - Constructor for class burlap.behavior.singleagent.planning.deterministic.uninformed.dfs.DFS
-
Basic constructor for standard DFS without a depth limit
- DFS(Domain, StateConditionTest, StateHashFactory, int) - Constructor for class burlap.behavior.singleagent.planning.deterministic.uninformed.dfs.DFS
-
Basic constructor for standard DFS with a depth limit
- DFS(Domain, StateConditionTest, StateHashFactory, int, boolean) - Constructor for class burlap.behavior.singleagent.planning.deterministic.uninformed.dfs.DFS
-
Constructor of DFS with specification of depth limit and whether to maintain a closed list that affects exploration.
- DFS(Domain, StateConditionTest, StateHashFactory, int, boolean, boolean) - Constructor for class burlap.behavior.singleagent.planning.deterministic.uninformed.dfs.DFS
-
Constructor of DFS with specification of depth limit, whether to maintain a closed list that affects exploration, and whether paths
generated by options should be explored first.
- dfs(SearchNode, int, Set<StateHashTuple>) - Method in class burlap.behavior.singleagent.planning.deterministic.uninformed.dfs.DFS
-
Runs DFS from a given search node, keeping track of its current depth.
- dfs(SearchNode, int, Set<StateHashTuple>) - Method in class burlap.behavior.singleagent.planning.deterministic.uninformed.dfs.LimitedMemoryDFS
-
Runs DFS from a given search node, keeping track of its current depth.
- DFSInit(Domain, TerminalFunction, StateConditionTest, StateHashFactory, int, boolean, boolean) - Method in class burlap.behavior.singleagent.planning.deterministic.uninformed.dfs.DFS
-
Constructor of DFS with specification of depth limit, whether to maintain a closed list that affects exploration, and whether paths
generated by options should be explored first.
- dheight - Variable in class burlap.domain.singleagent.gridworld.GridWorldVisualizer.CellPainter
-
- dheight - Variable in class burlap.domain.singleagent.gridworld.GridWorldVisualizer.LocationPainter
-
- dheight - Variable in class burlap.domain.singleagent.gridworld.GridWorldVisualizer.MapPainter
-
- dheight - Variable in class burlap.domain.singleagent.gridworld.macro.MacroCellVisualizer.MacroCellRewardWeightPainter
-
- DifferentiableRF - Class in burlap.behavior.singleagent.learnbydemo.mlirl.support
-
An abstract class for defining differentiable reward functions.
- DifferentiableRF() - Constructor for class burlap.behavior.singleagent.learnbydemo.mlirl.support.DifferentiableRF
-
- DifferentiableSparseSampling - Class in burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners
-
A Differentiable finite horizon planner that can also use sparse sampling over the transition dynamics when the
transition function is very large or infinite.
- DifferentiableSparseSampling(Domain, DifferentiableRF, TerminalFunction, double, StateHashFactory, int, int, double) - Constructor for class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.DifferentiableSparseSampling
-
Initializes.
- DifferentiableSparseSampling.DiffStateNode - Class in burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners
-
A class for value differentiable state nodes.
- DifferentiableSparseSampling.DiffStateNode(StateHashTuple, int) - Constructor for class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.DifferentiableSparseSampling.DiffStateNode
-
- DifferentiableSparseSampling.QAndQGradient - Class in burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners
-
A tuple for storing Q-values and their gradients.
- DifferentiableSparseSampling.QAndQGradient(List<QValue>, List<QGradientTuple>) - Constructor for class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.DifferentiableSparseSampling.QAndQGradient
-
- DifferentiableSparseSampling.QAndQGradient(int) - Constructor for class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.DifferentiableSparseSampling.QAndQGradient
-
- DifferentiableSparseSampling.VAndVGradient - Class in burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners
-
A tuple for storing a state value and its gradient.
- DifferentiableSparseSampling.VAndVGradient(double, double[]) - Constructor for class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.DifferentiableSparseSampling.VAndVGradient
-
- DifferentiableVFPlanner - Class in burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners
-
A class for performing dynamic programming based planning with a differentiable value backup operator.
- DifferentiableVFPlanner() - Constructor for class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.DifferentiableVFPlanner
-
- DifferentiableVI - Class in burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners
-
Performs Differentiable Value Iteration using the Boltzmann backup operator and a
DifferentiableRF.
- DifferentiableVI(Domain, DifferentiableRF, TerminalFunction, double, double, StateHashFactory, double, int) - Constructor for class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.DifferentiableVI
-
Initializes the planner.
- DifferentiableVInit - Interface in burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.diffvinit
-
An interface for value function initialization that is differentiable with respect to some parameters.
- DifferentiableVInit.ParamedDiffVInit - Class in burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.diffvinit
-
A abstract class for
DifferentiableVInit
that includes a double array of parameters and methods to modify them.
- DifferentiableVInit.ParamedDiffVInit() - Constructor for class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.diffvinit.DifferentiableVInit.ParamedDiffVInit
-
- DiffVFRF - Class in burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.diffvinit
-
A differentiable reward function wrapper for use with
MLIRL when
the reward function is known, but the value function initialization for leaf nodes is to be learned.
- DiffVFRF(RewardFunction, DifferentiableVInit.ParamedDiffVInit) - Constructor for class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.diffvinit.DiffVFRF
-
- diffVInit - Variable in class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.diffvinit.DiffVFRF
-
- dim - Variable in class burlap.behavior.singleagent.learnbydemo.mlirl.differentiableplanners.diffvinit.DifferentiableVInit.ParamedDiffVInit
-
The parameter dimensionality
- dim - Variable in class burlap.behavior.singleagent.learnbydemo.mlirl.support.DifferentiableRF
-
The parameter dimensionality
- dim - Variable in class burlap.behavior.singleagent.vfa.common.FVToFeatureDatabase
-
The dimensionality of the state features produced by the feature vector generator
- dimensionMask - Variable in class burlap.behavior.singleagent.vfa.cmac.FVTiling
-
The dimensions on which this tiling are dependent
- dir - Variable in class burlap.domain.singleagent.blockdude.BlockDude.MoveAction
-
- directEpisodes - Variable in class burlap.behavior.singleagent.EpisodeSequenceVisualizer
-
- directGames - Variable in class burlap.behavior.stochasticgame.GameSequenceVisualizer
-
- direction - Variable in class burlap.behavior.singleagent.auxiliary.valuefunctionvis.common.ArrowActionGlyph
-
The direction of the arrow.0: north; 1: south; 2: east; 3:west
- directionProbs - Variable in class burlap.domain.singleagent.frostbite.FrostbiteDomain.MovementAction
-
Probabilities of the actual direction the agent will go
- directionProbs - Variable in class burlap.domain.singleagent.gridworld.GridWorldDomain.MovementAction
-
Probabilities of the actual direction the agent will go
- DirectOptionTerminateMapper - Interface in burlap.behavior.singleagent.options
-
If an option deterministically terminates with a fixed number of steps, then it may be useful
for an option to immediately transition from the state in which the option was initiated to the
end terminal state, rather than having to simulate each step of execution.
- directory - Variable in class burlap.oomdp.singleagent.explorer.VisualExplorer.SaveEpisodeAction
-
The directory in which the episodes will be recorded.
- DISCATT - Static variable in class burlap.behavior.singleagent.interfaces.rlglue.RLGlueWrappedDomainGenerator
-
- discount - Variable in class burlap.behavior.singleagent.shaping.potential.PotentialShapedRF
-
The discount factor the MDP (required for this to shaping to preserve policy optimality)
- discount - Variable in class burlap.behavior.stochasticgame.agents.maql.MAQLFactory
-
- discount - Variable in class burlap.behavior.stochasticgame.agents.maql.MultiAgentQLearning
-
The discount factor
- discount - Variable in class burlap.behavior.stochasticgame.agents.mavf.MAVFPlannerFactory.MAVIPlannerFactory
-
The discount factor in [0, 1]
- discount - Variable in class burlap.behavior.stochasticgame.agents.naiveq.history.SGQWActionHistoryFactory
-
The discount rate the Q-learning algorithm will use
- discount - Variable in class burlap.behavior.stochasticgame.agents.naiveq.SGNaiveQFactory
-
The discount rate the Q-learning algorithm will use
- discount - Variable in class burlap.behavior.stochasticgame.agents.naiveq.SGNaiveQLAgent
-
The discount factor
- discount - Variable in class burlap.behavior.stochasticgame.mavaluefunction.MAValueFunctionPlanner
-
The discount factor in [0, 1]
- discount - Variable in class burlap.oomdp.singleagent.interfaces.rlglue.RLGlueEnvironment
-
The discount factor of the task
- discountFactor - Variable in class burlap.behavior.singleagent.options.Option
-
discount factor of the MDP in which this option will be applied
- DISCRETECLASS - Static variable in class burlap.behavior.singleagent.interfaces.rlglue.RLGlueWrappedDomainGenerator
-
- DiscreteMaskHashingFactory - Class in burlap.behavior.statehashing
-
Like the
DiscreteStateHashFactory (which this class extends) this class computes unique hash codes for states
based on attributes that the client specifies to use.
- DiscreteMaskHashingFactory() - Constructor for class burlap.behavior.statehashing.DiscreteMaskHashingFactory
-
Initializes this hashing factory to compute hash codes and equality checks with all attributes of all object classes.
- DiscreteMaskHashingFactory(Map<String, List<Attribute>>) - Constructor for class burlap.behavior.statehashing.DiscreteMaskHashingFactory
-
Initializes this hashing factory to hash and equality check on only the attributes for the specified classes in the provided map
- DiscreteMaskHashingFactory.DiscreteMaskHashTuple - Class in burlap.behavior.statehashing
-
- DiscreteMaskHashingFactory.DiscreteMaskHashTuple(State) - Constructor for class burlap.behavior.statehashing.DiscreteMaskHashingFactory.DiscreteMaskHashTuple
-
- DiscreteStateHashFactory - Class in burlap.behavior.statehashing
-
This hash factory will producing hash codes that are unique for discrete OO-MDP domains.
- DiscreteStateHashFactory() - Constructor for class burlap.behavior.statehashing.DiscreteStateHashFactory
-
Initializes this hashing factory to compute hash codes with all attributes of all object classes.
- DiscreteStateHashFactory(Map<String, List<Attribute>>) - Constructor for class burlap.behavior.statehashing.DiscreteStateHashFactory
-
Initializes this hashing factory to hash on only the attributes for the specified classes in the provided map
- DiscreteStateHashFactory.DiscreteStateHashTuple - Class in burlap.behavior.statehashing
-
- DiscreteStateHashFactory.DiscreteStateHashTuple(State) - Constructor for class burlap.behavior.statehashing.DiscreteStateHashFactory.DiscreteStateHashTuple
-
- DiscreteValue - Class in burlap.oomdp.core.values
-
A discrete value subclass in which discrete values are stored as int values.
- DiscreteValue(Attribute) - Constructor for class burlap.oomdp.core.values.DiscreteValue
-
Initializes this value to be an assignment for Attribute attribute.
- DiscreteValue(Value) - Constructor for class burlap.oomdp.core.values.DiscreteValue
-
Initializes this value as a copy from the source Value object v.
- DiscretizingStateHashFactory - Class in burlap.behavior.statehashing
-
This hashing factory is used for comparing states with continuous attributes as if they were discretized, thereby allowing discrete state planning/learning
algorithms to be used on domains with continuous attributes.
- DiscretizingStateHashFactory() - Constructor for class burlap.behavior.statehashing.DiscretizingStateHashFactory
-
Initializes.
- DiscretizingStateHashFactory(double) - Constructor for class burlap.behavior.statehashing.DiscretizingStateHashFactory
-
Initializes with a specified default multiple to use for discretization.
- DiscretizingStateHashFactory.DiscretizedStateHashTuple - Class in burlap.behavior.statehashing
-
- DiscretizingStateHashFactory.DiscretizedStateHashTuple(State) - Constructor for class burlap.behavior.statehashing.DiscretizingStateHashFactory.DiscretizedStateHashTuple
-
- discVal - Variable in class burlap.oomdp.core.values.DiscreteValue
-
The discrete value stored as an integer.
- discValues - Variable in class burlap.oomdp.core.Attribute
-
The possible categorical values for a discrete or boolean attribute.
- discValuesHash - Variable in class burlap.oomdp.core.Attribute
-
maps categorical names of discrete values to int values
- displayPlots - Variable in class burlap.behavior.singleagent.auxiliary.performance.LearningAlgorithmExperimenter
-
Whether the performance should be visually plotted (by default they will)
- displayPlots - Variable in class burlap.behavior.stochasticgame.auxiliary.performance.MultiAgentExperimenter
-
Whether the performance should be visually plotted (by default they will)
- distance(State, State) - Method in interface burlap.behavior.singleagent.vfa.rbf.DistanceMetric
-
- distance(double[], double[]) - Method in interface burlap.behavior.singleagent.vfa.rbf.FVDistanceMetric
-
Returns the distance between state s0 and state s1.
- distance(State, State) - Method in class burlap.behavior.singleagent.vfa.rbf.metrics.EuclideanDistance
-
- distance(double[], double[]) - Method in class burlap.behavior.singleagent.vfa.rbf.metrics.FVEuclideanDistance
-
- DistanceMetric - Interface in burlap.behavior.singleagent.vfa.rbf
-
An interface for defining distant metrics between OO-MDP
State objects.
- domain - Variable in class burlap.behavior.singleagent.auxiliary.performance.LearningAlgorithmExperimenter
-
The domain in which the agents will be tested.
- domain - Variable in class burlap.behavior.singleagent.auxiliary.StateEnumerator
-
The domain whose states will be enumerated
- domain - Variable in class burlap.behavior.singleagent.EpisodeSequenceVisualizer
-
- domain - Variable in class burlap.behavior.singleagent.interfaces.rlglue.RLGlueAgentShell
-
The BURLAP domain that wraps the RLGlue environment
- domain - Variable in class burlap.behavior.singleagent.interfaces.rlglue.RLGlueWrappedDomainGenerator
-
- domain - Variable in class burlap.behavior.singleagent.learnbydemo.IRLRequest
-
The domain in which IRL is to be performed
- domain - Variable in class burlap.behavior.singleagent.learning.actorcritic.actor.BoltzmannActor
-
The domain in which this agent will act
- domain - Variable in class burlap.behavior.singleagent.learning.modellearning.modelplanners.VIModelPlanner
-
the model domain
- domain - Variable in class burlap.behavior.singleagent.planning.OOMDPPlanner
-
The domain in which planning will be performed
- domain - Variable in class burlap.behavior.stochasticgame.agents.maql.MAQLFactory
-
- domain - Variable in class burlap.behavior.stochasticgame.agents.mavf.MAVFPlanAgentFactory
-
- domain - Variable in class burlap.behavior.stochasticgame.agents.mavf.MAVFPlannerFactory.MAVIPlannerFactory
-
The domain in which planning is to be performed
- domain - Variable in class burlap.behavior.stochasticgame.agents.naiveq.history.ParameterNaiveActionIdMap
-
The domain for which the action values should be created.
- domain - Variable in class burlap.behavior.stochasticgame.agents.naiveq.history.SGQWActionHistoryFactory
-
The stochastic games domain in which the agent will act
- domain - Variable in class burlap.behavior.stochasticgame.agents.naiveq.SGNaiveQFactory
-
The stochastic games domain in which the agent will act
- domain - Variable in class burlap.behavior.stochasticgame.agents.SetStrategyAgent.SetStrategyAgentFactory
-
The domain in which the agent will play
- domain - Variable in class burlap.behavior.stochasticgame.agents.twoplayer.repeatedsinglestage.GrimTrigger.GrimTriggerAgentFactory
-
The domain in which the agent will play
- domain - Variable in class burlap.behavior.stochasticgame.agents.twoplayer.repeatedsinglestage.TitForTat.TitForTatAgentFactory
-
The domain in which the agent will play
- domain - Variable in class burlap.behavior.stochasticgame.GameSequenceVisualizer
-
- domain - Variable in class burlap.behavior.stochasticgame.mavaluefunction.MAValueFunctionPlanner
-
The domain in which planning is to be performed
- domain - Variable in class burlap.domain.singleagent.cartpole.CartPoleStateParser
-
- domain - Variable in class burlap.domain.singleagent.cartpole.InvertedPendulumStateParser
-
- domain - Variable in class burlap.domain.singleagent.gridworld.GridWorldStateParser
-
- domain - Variable in class burlap.oomdp.auxiliary.common.StateJSONParser
-
The domain holding the object class definitions that states represented in JSON strings will be converted to.
- domain - Variable in class burlap.oomdp.auxiliary.common.StateYAMLParser
-
The domain holding the object class definitions that states represented in yaml strings will be converted to.
- domain - Variable in class burlap.oomdp.auxiliary.common.UniversalStateParser
-
- domain - Variable in class burlap.oomdp.core.Attribute
-
domain that holds this attribute
- Domain - Class in burlap.oomdp.core
-
This is the base class for an OO-MDP/OO-SG domain.
- Domain() - Constructor for class burlap.oomdp.core.Domain
-
Initializes the data structures for indexing the object classes, attributes, and propositional functions
- domain - Variable in class burlap.oomdp.core.ObjectClass
-
- domain - Variable in class burlap.oomdp.core.PropositionalFunction
-
- domain - Variable in class burlap.oomdp.singleagent.Action
-
The domain with which this action is associated
- domain - Variable in class burlap.oomdp.singleagent.common.VisualActionObserver
-
The domain this visualizer is rendering
- domain - Variable in class burlap.oomdp.singleagent.explorer.TerminalExplorer
-
- domain - Variable in class burlap.oomdp.singleagent.explorer.VisualExplorer
-
- domain - Variable in class burlap.oomdp.singleagent.interfaces.rlglue.RLGlueEnvironment
-
The BURLAP domain
- domain - Variable in class burlap.oomdp.stochasticgames.Agent
-
- domain - Variable in class burlap.oomdp.stochasticgames.common.VisualWorldObserver
-
The domain this visualizer is rendering
- domain - Variable in class burlap.oomdp.stochasticgames.explorers.SGTerminalExplorer
-
- domain - Variable in class burlap.oomdp.stochasticgames.SingleAction
-
- domain - Variable in class burlap.oomdp.stochasticgames.tournament.common.ConstantWorldGenerator
-
- domain - Variable in class burlap.oomdp.stochasticgames.World
-
- DomainEnvironmentWrapper - Class in burlap.oomdp.singleagent.environment
-
If a problem is best described by an Environment class, this domain wrapper takes a domain object
that specifies the state representation and action set, and creates a new domain object in which
actions of the same name and parameterization will make calls to the provided Environment class
and wait for it to return the resulting state before returning themselves.
- DomainEnvironmentWrapper(Domain, Environment) - Constructor for class burlap.oomdp.singleagent.environment.DomainEnvironmentWrapper
-
Initializes this class with the source domain used by an environment object
- domainGenerator - Variable in class burlap.behavior.singleagent.interfaces.rlglue.RLGlueAgentShell
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The BURLAP domain generator which can take as input an RLGlue task spec and produce a corresponding domain.
- DomainGenerator - Interface in burlap.oomdp.auxiliary
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This class provides a simple interface for constructing domains, but it is not required to create domains.
- DomainMappedPolicy - Class in burlap.behavior.singleagent.learning.modellearning
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In model learning, it is not uncommon to have a modeled domain object with its own actions that are distinct from the actual action objects in the world.
- DomainMappedPolicy(Domain, Policy) - Constructor for class burlap.behavior.singleagent.learning.modellearning.DomainMappedPolicy
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Initializes.
- domainWrapper - Variable in class burlap.behavior.stochasticgame.agents.interfacing.singleagent.SGToSADomain
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The singel agent domain object that will be returned
- dot(double[], double[]) - Static method in class burlap.behavior.stochasticgame.solvers.GeneralBimatrixSolverTools
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Returns the dot product of two vectors
- doubleArray - Variable in class burlap.oomdp.core.values.DoubleArrayValue
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- DoubleArrayValue - Class in burlap.oomdp.core.values
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This class implements an attribute value that is defined with a double array.
- DoubleArrayValue(Attribute) - Constructor for class burlap.oomdp.core.values.DoubleArrayValue
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- DoubleArrayValue(Value) - Constructor for class burlap.oomdp.core.values.DoubleArrayValue
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- doubleEpislon - Static variable in class burlap.behavior.stochasticgame.agents.twoplayer.singlestage.equilibriumplayer.BimatrixEquilibriumSolver
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The epislon difference used to test for double equality.
- doubleEquality(double, double) - Static method in class burlap.behavior.stochasticgame.agents.twoplayer.singlestage.equilibriumplayer.BimatrixEquilibriumSolver
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- dp - Variable in class burlap.behavior.singleagent.planning.deterministic.DDPlannerPolicy
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- dp - Variable in class burlap.behavior.singleagent.planning.deterministic.SDPlannerPolicy
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- DPrint - Class in burlap.debugtools
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A class for managing debug print statements.
- DPrint() - Constructor for class burlap.debugtools.DPrint
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- dwidth - Variable in class burlap.domain.singleagent.gridworld.GridWorldVisualizer.CellPainter
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- dwidth - Variable in class burlap.domain.singleagent.gridworld.GridWorldVisualizer.LocationPainter
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- dwidth - Variable in class burlap.domain.singleagent.gridworld.GridWorldVisualizer.MapPainter
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- dwidth - Variable in class burlap.domain.singleagent.gridworld.macro.MacroCellVisualizer.MacroCellRewardWeightPainter
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- DynamicWeightedAStar - Class in burlap.behavior.singleagent.planning.deterministic.informed.astar
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Dynamic Weighted A* [1] uses a dynamic heuristic weight that is based on depth of the current search tree and based on an expected depth of the search.
- DynamicWeightedAStar(Domain, RewardFunction, StateConditionTest, StateHashFactory, Heuristic, double, int) - Constructor for class burlap.behavior.singleagent.planning.deterministic.informed.astar.DynamicWeightedAStar
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Initializes the planner.