- tabDomain - Variable in class burlap.domain.singleagent.tabularized.TabulatedDomainWrapper
-
The output tabularied domain
- TabularBeliefState - Class in burlap.oomdp.singleagent.pomdp.beliefstate.tabular
-
A class for storing a sparse tabular representation of the belief state.
- TabularBeliefState(TabularBeliefState) - Constructor for class burlap.oomdp.singleagent.pomdp.beliefstate.tabular.TabularBeliefState
-
- TabularBeliefState(PODomain) - Constructor for class burlap.oomdp.singleagent.pomdp.beliefstate.tabular.TabularBeliefState
-
- TabularBeliefState(PODomain, StateEnumerator) - Constructor for class burlap.oomdp.singleagent.pomdp.beliefstate.tabular.TabularBeliefState
-
- TabularModel - Class in burlap.behavior.singleagent.learning.modellearning.models
-
A tabular model using frequencies to model the transition dynamics.
- TabularModel(Domain, HashableStateFactory, int) - Constructor for class burlap.behavior.singleagent.learning.modellearning.models.TabularModel
-
Initializes.
- TabulatedDomainWrapper - Class in burlap.domain.singleagent.tabularized
-
In general, it is suggested algorithms be designed to work with either factored state representations or the BURLAP State Hashing.
- TabulatedDomainWrapper(Domain, HashableStateFactory) - Constructor for class burlap.domain.singleagent.tabularized.TabulatedDomainWrapper
-
Constructs.
- TabulatedDomainWrapper.ActionWrapper - Class in burlap.domain.singleagent.tabularized
-
An action wrapper that coverts a tabularized state into the source domain state, perform the corresponding source domain action on it getting the
resulting source domain state and returns the tabularized version of the resulting source domain state.
- TabulatedDomainWrapper.ActionWrapper(Domain, Action) - Constructor for class burlap.domain.singleagent.tabularized.TabulatedDomainWrapper.ActionWrapper
-
Constructs
- target - Variable in class burlap.oomdp.core.values.RelationalValue
-
A string representing the object target of this value.
- targetAgentQName - Variable in class burlap.behavior.stochasticgames.madynamicprogramming.policies.EGreedyJointPolicy
-
The agent whose q-values dictate which joint actions to return
- targetAgentQName - Variable in class burlap.behavior.stochasticgames.madynamicprogramming.policies.EMinMaxPolicy
-
The target agent who is maximizing action selection
- targetDomain - Variable in class burlap.behavior.policy.DomainMappedPolicy
-
The target domain containing the target actions that need to be selected.
- targetObjects - Variable in class burlap.oomdp.core.values.MultiTargetRelationalValue
-
The set of object targets to which this value points.
- TaskSettableEnvironment - Interface in burlap.oomdp.singleagent.environment
-
- TATTNAME - Static variable in class burlap.domain.singleagent.lunarlander.LunarLanderDomain
-
Constant for the name of the top boundary attribute for rectangular obstacles and landing pads
- TDLambda - Class in burlap.behavior.singleagent.learning.actorcritic.critics
-
An implementation of TDLambda that can be used as a critic for
ActorCritic algorithms [1].
- TDLambda(RewardFunction, TerminalFunction, double, HashableStateFactory, double, double, double) - Constructor for class burlap.behavior.singleagent.learning.actorcritic.critics.TDLambda
-
Initializes the algorithm.
- TDLambda(RewardFunction, TerminalFunction, double, HashableStateFactory, double, ValueFunctionInitialization, double) - Constructor for class burlap.behavior.singleagent.learning.actorcritic.critics.TDLambda
-
Initializes the algorithm.
- TDLambda.StateEligibilityTrace - Class in burlap.behavior.singleagent.learning.actorcritic.critics
-
A data structure for storing the elements of an eligibility trace.
- TDLambda.StateEligibilityTrace(HashableState, double, TDLambda.VValue) - Constructor for class burlap.behavior.singleagent.learning.actorcritic.critics.TDLambda.StateEligibilityTrace
-
Initializes with hashed state, eligibility value and the value function value associated with the state.
- teardown() - Method in class burlap.testing.TestBlockDude
-
- teardown() - Method in class burlap.testing.TestGridWorld
-
- teardown() - Method in class burlap.testing.TestImmutableState
-
- teardown() - Method in class burlap.testing.TestPlanning
-
- temperature - Variable in class burlap.datastructures.BoltzmannDistribution
-
The temperature value.
- tempNormalized - Variable in class burlap.datastructures.BoltzmannDistribution
-
The preference values normalized by the temperature
- TerminalExplorer - Class in burlap.oomdp.singleagent.explorer
-
Deprecated.
- TerminalExplorer(Domain, State) - Constructor for class burlap.oomdp.singleagent.explorer.TerminalExplorer
-
Deprecated.
- TerminalExplorer(Domain, Environment) - Constructor for class burlap.oomdp.singleagent.explorer.TerminalExplorer
-
Deprecated.
Initializes.
- terminalFunction - Variable in class burlap.behavior.stochasticgames.agents.madp.MADPPlannerFactory.MAVIPlannerFactory
-
The state terminal function.
- terminalFunction - Variable in class burlap.behavior.stochasticgames.madynamicprogramming.MADynamicProgramming
-
The state terminal function.
- TerminalFunction - Interface in burlap.oomdp.core
-
And interface for defining terminal states of an MDP.
- terminalPositions - Variable in class burlap.domain.singleagent.gridworld.GridWorldTerminalFunction
-
The set of positions marked as terminal positions.
- terminalStates - Variable in class burlap.behavior.singleagent.learning.modellearning.models.TabularModel
-
The set of states marked as terminal states.
- terminalStates - Variable in class burlap.domain.singleagent.graphdefined.GraphTF
-
The set of nodes ids in the graph that are terminal states
- terminalVisits - Variable in class burlap.oomdp.singleagent.interfaces.rlglue.RLGlueEnvironment
-
Indicates the number of times a terminal state has been visited by the agent within the same episode.
- terminated - Variable in class burlap.oomdp.singleagent.environment.EnvironmentOutcome
-
Whether the next state to which the environment transitioned is a terminal state (true if so, false otherwise)
- terminateMapper - Variable in class burlap.behavior.singleagent.options.Option
-
An optional mapping from initiation states to terminal states so that the execution of an option does not need to be simulated.
- test1() - Static method in class burlap.datastructures.StochasticTree
-
Another example usage
- test2() - Static method in class burlap.datastructures.StochasticTree
-
An example usage
- testAddition() - Method in class burlap.testing.TestTesting
-
- testAStar() - Method in class burlap.testing.TestPlanning
-
- testBFS() - Method in class burlap.testing.TestPlanning
-
- TestBlockDude - Class in burlap.testing
-
- TestBlockDude() - Constructor for class burlap.testing.TestBlockDude
-
- testDFS() - Method in class burlap.testing.TestPlanning
-
- testDude() - Method in class burlap.testing.TestBlockDude
-
- testDude(State) - Method in class burlap.testing.TestBlockDude
-
- testEnvironment - Variable in class burlap.behavior.singleagent.auxiliary.performance.LearningAlgorithmExperimenter
-
The test
Environment in which experiments will be performed.
- testFixedSizeImmutableStateGridWorld() - Method in class burlap.testing.TestImmutableState
-
- TestGridWorld - Class in burlap.testing
-
- TestGridWorld() - Constructor for class burlap.testing.TestGridWorld
-
- testGridWorld() - Method in class burlap.testing.TestGridWorld
-
- testGridWorld(State) - Method in class burlap.testing.TestGridWorld
-
- TestHashing - Class in burlap.testing
-
- TestHashing() - Constructor for class burlap.testing.TestHashing
-
- testHashingScheme() - Method in class burlap.testing.TestHashing
-
- testImmutableSimpleHashFactoryIdentifierDependentCached() - Method in class burlap.testing.TestHashing
-
- TestImmutableState - Class in burlap.testing
-
- TestImmutableState() - Constructor for class burlap.testing.TestImmutableState
-
- testImmutableStateGridWorld() - Method in class burlap.testing.TestImmutableState
-
- TestPlanning - Class in burlap.testing
-
- TestPlanning() - Constructor for class burlap.testing.TestPlanning
-
- TestRunner - Class in burlap.testing
-
- TestRunner() - Constructor for class burlap.testing.TestRunner
-
- testSimpleHashFactory() - Method in class burlap.testing.TestHashing
-
- testSimpleHashFactoryCached() - Method in class burlap.testing.TestHashing
-
- testSimpleHashFactoryIdentifierDependent() - Method in class burlap.testing.TestHashing
-
- testSimpleHashFactoryIdentifierDependentCached() - Method in class burlap.testing.TestHashing
-
- testSimpleHashFactoryIdentifierIndependent() - Method in class burlap.testing.TestHashing
-
- testSimpleHashFactoryLargeState() - Method in class burlap.testing.TestHashing
-
- testSimpleHashFactoryLargeState(HashableStateFactory, int, int, boolean) - Method in class burlap.testing.TestHashing
-
- testSimpleHashFactoryLargeStateIdentifierDependent() - Method in class burlap.testing.TestHashing
-
- TestSuite - Class in burlap.testing
-
- TestSuite() - Constructor for class burlap.testing.TestSuite
-
- TestTesting - Class in burlap.testing
-
- TestTesting() - Constructor for class burlap.testing.TestTesting
-
- TextAreaStreams - Class in burlap.oomdp.singleagent.explorer
-
Object that provides an InputStream and OutputStream that affect the content
of a JTextArea.
- TextAreaStreams(JTextArea) - Constructor for class burlap.oomdp.singleagent.explorer.TextAreaStreams
-
- TextAreaStreams.TextIn - Class in burlap.oomdp.singleagent.explorer
-
- TextAreaStreams.TextIn() - Constructor for class burlap.oomdp.singleagent.explorer.TextAreaStreams.TextIn
-
- TextAreaStreams.TextOut - Class in burlap.oomdp.singleagent.explorer
-
- TextAreaStreams.TextOut() - Constructor for class burlap.oomdp.singleagent.explorer.TextAreaStreams.TextOut
-
- tf - Variable in class burlap.behavior.singleagent.learnfromdemo.mlirl.support.QGradientPlannerFactory.DifferentiableVIFactory
-
The terminal function that the valueFunction uses.
- tf - Variable in class burlap.behavior.singleagent.learning.actorcritic.critics.TDLambda
-
The state termination function to indicate end states
- tf - Variable in class burlap.behavior.singleagent.MDPSolver
-
The terminal function for identifying terminal states
- tf - Variable in class burlap.behavior.stochasticgames.auxiliary.performance.MultiAgentExperimenter
-
The terminal function defining when episodes in a trial end
- tf - Variable in class burlap.behavior.stochasticgames.auxiliary.performance.MultiAgentPerformancePlotter
-
Terminal funciton for determining when episodes have ended.
- tf - Variable in class burlap.oomdp.auxiliary.stateconditiontest.TFGoalCondition
-
- tf - Variable in class burlap.oomdp.singleagent.environment.SimulatedEnvironment
-
The terminal function for this environment
- tf - Variable in class burlap.oomdp.singleagent.interfaces.rlglue.RLGlueEnvironment
-
The terminal function
- tf - Variable in class burlap.oomdp.stochasticgames.tournament.common.ConstantWorldGenerator
-
- tf - Variable in class burlap.oomdp.stochasticgames.World
-
- TFGoalCondition - Class in burlap.oomdp.auxiliary.stateconditiontest
-
A simple StateConditionTest wrapper of TerminalFunciton.
- TFGoalCondition(TerminalFunction) - Constructor for class burlap.oomdp.auxiliary.stateconditiontest.TFGoalCondition
-
Sets this class to return true on any states that are terminal states as indicated by the TerminalFunction.
- theTaskSpec - Variable in class burlap.behavior.singleagent.interfaces.rlglue.RLGlueDomain
-
The
TaskSpec used to generate the BURLAP
Domain
- tHistory - Variable in class burlap.behavior.singleagent.learnfromdemo.apprenticeship.ApprenticeshipLearningRequest
-
the history of scores across each reward function improvement
- threshold - Variable in class burlap.domain.singleagent.mountaincar.MountainCar.ClassicMCTF
-
- thrustValue - Variable in class burlap.domain.singleagent.lunarlander.LunarLanderDomain.ActionThrust
-
- thrustValues - Variable in class burlap.domain.singleagent.lunarlander.LunarLanderDomain
-
List of the thrust forces for each thrust action
- TigerDomain - Class in burlap.domain.singleagent.pomdp.tiger
-
An implementation of the classic Tiger domain.
- TigerDomain() - Constructor for class burlap.domain.singleagent.pomdp.tiger.TigerDomain
-
Initializes.
- TigerDomain(boolean) - Constructor for class burlap.domain.singleagent.pomdp.tiger.TigerDomain
-
Initializes.
- TigerDomain(boolean, double) - Constructor for class burlap.domain.singleagent.pomdp.tiger.TigerDomain
-
Initializes
- TigerDomain.OpenAction - Class in burlap.domain.singleagent.pomdp.tiger
-
Specifies an action for opening a door.
- TigerDomain.OpenAction(String, Domain) - Constructor for class burlap.domain.singleagent.pomdp.tiger.TigerDomain.OpenAction
-
- TigerDomain.TigerObservations - Class in burlap.domain.singleagent.pomdp.tiger
-
Defines the Tiger domain observation function
- TigerDomain.TigerObservations(PODomain, double) - Constructor for class burlap.domain.singleagent.pomdp.tiger.TigerDomain.TigerObservations
-
- TigerDomain.TigerRF - Class in burlap.domain.singleagent.pomdp.tiger
-
Defines the reward function for the tiger domain, which is defined by four values:
opening the correct door with the prize; opening the wrong door with the tiger; listening; and doing nothing.
- TigerDomain.TigerRF() - Constructor for class burlap.domain.singleagent.pomdp.tiger.TigerDomain.TigerRF
-
- tigerLeftState(PODomain) - Static method in class burlap.domain.singleagent.pomdp.tiger.TigerDomain
-
Returns the hidden state for when the tiger is behind the left door
- tigerRightState(PODomain) - Static method in class burlap.domain.singleagent.pomdp.tiger.TigerDomain
-
Returns the hidden state for when the tiger is behind the right door
- tiledObjectsByClass - Variable in class burlap.behavior.singleagent.vfa.cmac.Tiling.StateTile
-
The tiled version of object instances in the state
- tiledVector - Variable in class burlap.behavior.singleagent.vfa.cmac.FVTiling.FVTile
-
- tilesForLastState - Variable in class burlap.behavior.singleagent.vfa.cmac.CMACFeatureDatabase
-
- Tiling - Class in burlap.behavior.singleagent.vfa.cmac
-
This class provides a tiling specification, which tiles a state according to multi-dimensional tiling of specified attributes
for specified object classes.
- Tiling() - Constructor for class burlap.behavior.singleagent.vfa.cmac.Tiling
-
Initializes an empty tiling with not attribute specifications.
- Tiling.ObjectTile - Class in burlap.behavior.singleagent.vfa.cmac
-
A class for creating a tiling of a single OO-MDP object instance which will be combined with other object instance tiles
to create a single state tiling.
- Tiling.ObjectTile(ObjectInstance) - Constructor for class burlap.behavior.singleagent.vfa.cmac.Tiling.ObjectTile
-
Creates a tile for the given object instance
- Tiling.StateTile - Class in burlap.behavior.singleagent.vfa.cmac
-
A class for representing a tile, which can be treated as a state feature.
- Tiling.StateTile(State) - Constructor for class burlap.behavior.singleagent.vfa.cmac.Tiling.StateTile
-
Creates a state tile for the given input state
- tilings - Variable in class burlap.behavior.singleagent.vfa.cmac.CMACFeatureDatabase
-
The set of tilings for producing state features
- timeDelta - Variable in class burlap.domain.singleagent.cartpole.CartPoleDomain.CPPhysicsParams
-
The time between each action selection
- timeDelta - Variable in class burlap.domain.singleagent.cartpole.InvertedPendulum.IPPhysicsParams
-
The time between each action selection
- timeDelta - Variable in class burlap.domain.singleagent.mountaincar.MountainCar.MCPhysicsParams
-
The time difference to pass in each update
- timeIndex - Variable in class burlap.behavior.singleagent.learning.actorcritic.critics.TimeIndexedTDLambda.StateTimeElibilityTrace
-
The time/depth of the state this eligibility represents.
- TimeIndexedTDLambda - Class in burlap.behavior.singleagent.learning.actorcritic.critics
-
An implementation of TDLambda that can be used as a critic for
ActorCritic algorithms [1], except
that this class treats states at different depths as unique states.
- TimeIndexedTDLambda(RewardFunction, TerminalFunction, double, HashableStateFactory, double, double, double) - Constructor for class burlap.behavior.singleagent.learning.actorcritic.critics.TimeIndexedTDLambda
-
Initializes the algorithm.
- TimeIndexedTDLambda(RewardFunction, TerminalFunction, double, HashableStateFactory, double, double, double, int) - Constructor for class burlap.behavior.singleagent.learning.actorcritic.critics.TimeIndexedTDLambda
-
Initializes the algorithm.
- TimeIndexedTDLambda(RewardFunction, TerminalFunction, double, HashableStateFactory, double, ValueFunctionInitialization, double, int) - Constructor for class burlap.behavior.singleagent.learning.actorcritic.critics.TimeIndexedTDLambda
-
Initializes the algorithm.
- TimeIndexedTDLambda.StateTimeElibilityTrace - Class in burlap.behavior.singleagent.learning.actorcritic.critics
-
- TimeIndexedTDLambda.StateTimeElibilityTrace(HashableState, int, double, TDLambda.VValue) - Constructor for class burlap.behavior.singleagent.learning.actorcritic.critics.TimeIndexedTDLambda.StateTimeElibilityTrace
-
Initializes with hashed state, eligibility value, time/depth of the state, and the value function value associated with the state.
- tin - Variable in class burlap.oomdp.singleagent.explorer.TextAreaStreams
-
- TitForTat - Class in burlap.behavior.stochasticgames.agents.twoplayer.repeatedsinglestage
-
A class for an agent that plays tit-for-tat.
- TitForTat(SGDomain, SGAgentAction, SGAgentAction) - Constructor for class burlap.behavior.stochasticgames.agents.twoplayer.repeatedsinglestage.TitForTat
-
Initializes with the specified cooperate and defect actions for both players.
- TitForTat(SGDomain, SGAgentAction, SGAgentAction, SGAgentAction, SGAgentAction) - Constructor for class burlap.behavior.stochasticgames.agents.twoplayer.repeatedsinglestage.TitForTat
-
Initializes with differently specified cooperate and defect actions for both players.
- TitForTat.TitForTatAgentFactory - Class in burlap.behavior.stochasticgames.agents.twoplayer.repeatedsinglestage
-
An agent factory for a TitForTat player.
- TitForTat.TitForTatAgentFactory(SGDomain, SGAgentAction, SGAgentAction) - Constructor for class burlap.behavior.stochasticgames.agents.twoplayer.repeatedsinglestage.TitForTat.TitForTatAgentFactory
-
Initializes with the specified cooperate and defect actions for both players.
- TitForTat.TitForTatAgentFactory(SGDomain, SGAgentAction, SGAgentAction, SGAgentAction, SGAgentAction) - Constructor for class burlap.behavior.stochasticgames.agents.twoplayer.repeatedsinglestage.TitForTat.TitForTatAgentFactory
-
Initializes with differently specified cooperate and defect actions for both players.
- toggleBatchMode(boolean) - Method in class burlap.behavior.singleagent.planning.stochastic.rtdp.RTDP
-
When batch mode is set, Bellman updates will be stalled until a roll out is complete and then run in reverse.
- toggleCode(int, boolean) - Static method in class burlap.debugtools.DPrint
-
Enables/disables print commands to the given debug code
- toggleDataCollection(boolean) - Method in class burlap.behavior.singleagent.auxiliary.performance.PerformancePlotter
-
Toggle whether performance data collected from the action observation is recorded or not
- toggleDataCollection(boolean) - Method in class burlap.behavior.stochasticgames.auxiliary.performance.MultiAgentPerformancePlotter
-
Toggle whether performance data collected from the action observation is recorded or not
- toggleDebug(boolean) - Method in class burlap.behavior.singleagent.interfaces.rlglue.RLGlueEnvironmentInterface
-
Toggles whether debug information should be printed
- toggleDebugPrinting(boolean) - Method in class burlap.behavior.singleagent.learnfromdemo.mlirl.MLIRL
-
Sets whether information during learning is printed to the terminal.
- toggleDebugPrinting(boolean) - Method in class burlap.behavior.singleagent.learnfromdemo.mlirl.MultipleIntentionsMLIRL
-
Sets whether information during learning is printed to the terminal.
- toggleDebugPrinting(boolean) - Method in class burlap.behavior.singleagent.MDPSolver
-
- toggleDebugPrinting(boolean) - Method in interface burlap.behavior.singleagent.MDPSolverInterface
-
Toggles whether the solver's calls to
DPrint should be printed.
- toggleDebugPrinting(boolean) - Method in class burlap.oomdp.core.Domain
-
Toggles whether debug messages are printed
- toggleReachabiltiyTerminalStatePruning(boolean) - Method in class burlap.behavior.singleagent.learnfromdemo.mlirl.differentiableplanners.DifferentiableVI
-
Sets whether the state reachability search to generate the state space will be prune the search from terminal states.
- toggleReachabiltiyTerminalStatePruning(boolean) - Method in class burlap.behavior.singleagent.planning.stochastic.valueiteration.ValueIteration
-
Sets whether the state reachability search to generate the state space will be prune the search from terminal states.
- toggleShouldAnnotateOptionDecomposition(boolean) - Method in class burlap.behavior.singleagent.learning.tdmethods.QLearning
-
Sets whether options that are decomposed into primitives will have the option that produced them and listed.
- toggleShouldAnnotateOptionDecomposition(boolean) - Method in class burlap.behavior.singleagent.learning.tdmethods.vfa.GradientDescentSarsaLam
-
Sets whether options that are decomposed into primitives will have the option that produced them and listed.
- toggleShouldAnnotateResults(boolean) - Method in class burlap.behavior.singleagent.options.Option
-
Toggle whether the last recorded option execution will annotate the actions taken with this option's name
- toggleShouldDecomposeOption(boolean) - Method in class burlap.behavior.singleagent.learning.tdmethods.QLearning
-
Sets whether the primitive actions taken during an options will be included as steps in produced EpisodeAnalysis objects.
- toggleShouldDecomposeOption(boolean) - Method in class burlap.behavior.singleagent.learning.tdmethods.vfa.GradientDescentSarsaLam
-
Sets whether the primitive actions taken during an options will be included as steps in produced EpisodeAnalysis objects.
- toggleShouldRecordResults(boolean) - Method in class burlap.behavior.singleagent.options.Option
-
Change whether the options last execution will be recorded or not.
- toggleTrialLengthInterpretation(boolean) - Method in class burlap.behavior.singleagent.auxiliary.performance.LearningAlgorithmExperimenter
-
Changes whether the trial length provided in the constructor is interpreted as the number of episodes or total number of steps.
- toggleTrialLengthInterpretation(boolean) - Method in class burlap.behavior.stochasticgames.auxiliary.performance.MultiAgentExperimenter
-
Changes whether the trial length provided in the constructor is interpreted as the number of episodes or total number of steps.
- toggleUniversal(boolean) - Static method in class burlap.debugtools.DPrint
-
Specify whether previously unset debug codes will by default be allowed to print or not.
- toggleUseCachedTransitionDynamics(boolean) - Method in class burlap.behavior.singleagent.planning.stochastic.DynamicProgramming
-
Sets whether this object should cache hashed transition dynamics for each for faster look up, or whether
to procedurally generate the transition dynamics as needed from the
Action objects.
- toggleValueStringRendering(boolean) - Method in class burlap.behavior.singleagent.auxiliary.valuefunctionvis.common.StateValuePainter2D
-
Enables or disables the rendering the text specifying the value of a state in its cell.
- toggleVisualPlots(boolean) - Method in class burlap.behavior.singleagent.auxiliary.performance.LearningAlgorithmExperimenter
-
Toggles whether plots should be displayed or not.
- toggleVisualPlots(boolean) - Method in class burlap.behavior.stochasticgames.auxiliary.performance.MultiAgentExperimenter
-
Toggles whether plots should be displayed or not.
- toInt() - Method in enum burlap.behavior.singleagent.auxiliary.valuefunctionvis.common.PolicyGlyphPainter2D.PolicyGlyphRenderStyle
-
- toInt() - Method in enum burlap.behavior.singleagent.vfa.cmac.CMACFeatureDatabase.TilingArrangement
-
- toInt() - Method in enum burlap.oomdp.core.Attribute.AttributeType
-
- toString() - Method in class burlap.behavior.policy.Policy.ActionProb
-
- toString() - Method in class burlap.behavior.policy.Policy.GroundedAnnotatedAction
-
- toString() - Method in class burlap.behavior.singleagent.learnfromdemo.mlirl.commonrfs.LinearStateActionDifferentiableRF
-
- toString() - Method in class burlap.behavior.singleagent.learnfromdemo.mlirl.commonrfs.LinearStateDifferentiableRF
-
- toString() - Method in class burlap.behavior.stochasticgames.agents.interfacing.singleagent.SGToSADomain.GroundedSAAActionWrapper
-
- toString() - Method in class burlap.domain.stochasticgames.normalform.SingleStageNormalFormGame.StrategyProfile
-
- toString() - Method in class burlap.oomdp.core.GroundedProp
-
Returns a string representation of this grounded prop.
- toString() - Method in class burlap.oomdp.core.objects.ImmutableObjectInstance
-
- toString() - Method in class burlap.oomdp.core.PropositionalFunction
-
- toString() - Method in class burlap.oomdp.core.states.MutableState
-
- toString() - Method in class burlap.oomdp.core.states.OOMDPState
-
- toString() - Method in class burlap.oomdp.core.values.OOMDPValue
-
- toString() - Method in class burlap.oomdp.singleagent.GroundedAction
-
- toString() - Method in class burlap.oomdp.singleagent.ObjectParameterizedAction.ObjectParameterizedGroundedAction
-
- toString() - Method in class burlap.oomdp.singleagent.pomdp.BeliefMDPGenerator.GroundedBeliefAction
-
- toString() - Method in class burlap.oomdp.stochasticgames.agentactions.GroundedSGAgentAction
-
- toString() - Method in class burlap.oomdp.stochasticgames.agentactions.ObParamSGAgentAction.GroundedObParamSGAgentAction
-
- toString() - Method in class burlap.oomdp.stochasticgames.JointAction
-
- totalEpisodes - Variable in class burlap.behavior.singleagent.auxiliary.performance.PerformancePlotter.Trial
-
The total number of episodes in the trial
- totalEpisodes - Variable in class burlap.behavior.stochasticgames.auxiliary.performance.MultiAgentPerformancePlotter.Trial
-
The total number of episodes in the trial
- totalNumberOfSteps - Variable in class burlap.behavior.singleagent.learning.actorcritic.actor.BoltzmannActor
-
The total number of learning steps performed by this agent.
- totalNumberOfSteps - Variable in class burlap.behavior.singleagent.learning.actorcritic.critics.TDLambda
-
The total number of learning steps performed by this agent.
- totalNumberOfSteps - Variable in class burlap.behavior.singleagent.learning.tdmethods.QLearning
-
The total number of learning steps performed by this agent.
- totalNumberOfSteps - Variable in class burlap.behavior.singleagent.learning.tdmethods.vfa.GradientDescentSarsaLam
-
The total number of learning steps performed by this agent.
- totalNumberOfSteps - Variable in class burlap.behavior.stochasticgames.agents.maql.MultiAgentQLearning
-
The total number of learning steps performed by this agent.
- totalNumberOfSteps - Variable in class burlap.behavior.stochasticgames.agents.naiveq.SGNaiveQLAgent
-
The total number of learning steps performed by this agent.
- totalPolicyIterations - Variable in class burlap.behavior.singleagent.planning.stochastic.policyiteration.PolicyIteration
-
The total number of policy iterations performed
- totalSteps - Variable in class burlap.behavior.singleagent.auxiliary.performance.PerformancePlotter.Trial
-
the total number of steps in the trial
- totalSteps - Variable in class burlap.behavior.stochasticgames.auxiliary.performance.MultiAgentPerformancePlotter.Trial
-
the total number of steps in the trial
- totalValueIterations - Variable in class burlap.behavior.singleagent.planning.stochastic.policyiteration.PolicyIteration
-
The total number of value iterations used to evaluated policies performed
- touchingPad - Variable in class burlap.domain.singleagent.lunarlander.LunarLanderRF
-
- touchingSurface - Variable in class burlap.domain.singleagent.lunarlander.LunarLanderRF
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- Tournament - Class in burlap.oomdp.stochasticgames.tournament
-
This class is designed to run tournaments of sets of users.
- Tournament(int, MatchSelector, WorldGenerator) - Constructor for class burlap.oomdp.stochasticgames.tournament.Tournament
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Initializes the Tournament
- Tournament(int, int, MatchSelector, WorldGenerator) - Constructor for class burlap.oomdp.stochasticgames.tournament.Tournament
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Initializes the Tournament
- Tournament(List<AgentFactory>, int, MatchSelector, WorldGenerator) - Constructor for class burlap.oomdp.stochasticgames.tournament.Tournament
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Initializes the Tournament
- Tournament(List<AgentFactory>, int, int, MatchSelector, WorldGenerator) - Constructor for class burlap.oomdp.stochasticgames.tournament.Tournament
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Initializes the Tournament
- tournamentCumulatedReward - Variable in class burlap.oomdp.stochasticgames.tournament.Tournament
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- tout - Variable in class burlap.oomdp.singleagent.explorer.TextAreaStreams
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- tps - Variable in class burlap.behavior.stochasticgames.madynamicprogramming.MADynamicProgramming.JointActionTransitions
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- traces - Variable in class burlap.behavior.singleagent.learning.actorcritic.critics.TDLambda
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The eligibility traces for the current episode.
- train(List<SupervisedVFA.SupervisedVFAInstance>) - Method in interface burlap.behavior.singleagent.planning.vfa.fittedvi.SupervisedVFA
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Uses supervised learning (regression) to learn a value function approximation of the input training data.
- train(List<SupervisedVFA.SupervisedVFAInstance>) - Method in class burlap.behavior.singleagent.planning.vfa.fittedvi.WekaVFATrainer
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- transitionDynamics - Variable in class burlap.behavior.singleagent.planning.stochastic.DynamicProgramming
-
A data structure for storing the hashed transition dynamics from each state, if this algorithm is set to use them.
- transitionDynamics - Variable in class burlap.domain.singleagent.frostbite.FrostbiteDomain
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Matrix specifying the transition dynamics in terms of movement directions.
- transitionDynamics - Variable in class burlap.domain.singleagent.graphdefined.GraphDefinedDomain.GraphAction
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The transition dynamics to use
- transitionDynamics - Variable in class burlap.domain.singleagent.graphdefined.GraphDefinedDomain
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The state-action stochastic transition dynamics from each state node.
- transitionDynamics - Variable in class burlap.domain.singleagent.gridworld.GridWorldDomain
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Matrix specifying the transition dynamics in terms of movement directions.
- transitionIsModeled(State, GroundedAction) - Method in class burlap.behavior.singleagent.learning.modellearning.Model
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Indicates whether this model "knows" how the transition dynamics from the given input state and action work.
- transitionIsModeled(State, GroundedAction) - Method in class burlap.behavior.singleagent.learning.modellearning.models.TabularModel
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- TransitionProbability - Class in burlap.oomdp.core
-
Represents the probability of transition to a given state.
- TransitionProbability(State, double) - Constructor for class burlap.oomdp.core.TransitionProbability
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- transitionProbsFor(State, JointAction) - Method in class burlap.domain.stochasticgames.gridgame.GridGameStandardMechanics
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- transitionProbsFor(State, JointAction) - Method in class burlap.oomdp.stochasticgames.common.StaticRepeatedGameActionModel
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- transitionProbsFor(State, JointAction) - Method in class burlap.oomdp.stochasticgames.JointActionModel
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Returns the transition probabilities for applying the provided
JointAction action in the given state.
- transitions - Variable in class burlap.behavior.singleagent.planning.stochastic.ActionTransitions
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- transitionSamples - Variable in class burlap.behavior.singleagent.planning.vfa.fittedvi.FittedVI
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The number of transition samples used when computing the bellman operator.
- transitionTo - Variable in class burlap.domain.singleagent.graphdefined.GraphDefinedDomain.NodeTransitionProbability
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The resulting state
- translateAction(GroundedAction, Map<String, String>) - Method in class burlap.behavior.singleagent.MDPSolver
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Takes a source GroundedAction and a matching between object instances of two different states and returns a GroundedAction
with parameters using the matched parameters if the GroundedAction is an instance of
AbstractObjectParameterizedGroundedAction.
- translateAction(GroundedSGAgentAction, Map<String, String>) - Method in class burlap.behavior.stochasticgames.agents.naiveq.SGNaiveQLAgent
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Takes an input action and mapping objects in the source state for the action to objects in another state
and returns a action with its object parameters mapped to the matched objects.
- translateParameters(State, State) - Method in class burlap.behavior.policy.Policy.GroundedAnnotatedAction
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- translateParameters(State, State) - Method in class burlap.behavior.stochasticgames.agents.interfacing.singleagent.SGToSADomain.GroundedSAAActionWrapper
-
- translateParameters(AbstractGroundedAction, State, State) - Static method in class burlap.oomdp.core.AbstractObjectParameterizedGroundedAction.Helper
-
This method will translate this object's parameters that were assigned for a given source state, into object parameters in the
target state that are equal.
- translateParameters(State, State) - Method in class burlap.oomdp.singleagent.GroundedAction
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- translateParameters(State, State) - Method in class burlap.oomdp.stochasticgames.JointAction
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- transposeMatrix(double[][]) - Static method in class burlap.behavior.stochasticgames.solvers.GeneralBimatrixSolverTools
-
Creates and returns a new matrix that is a transpose of m.
- treeRollOut(UCTStateNode, int, int) - Method in class burlap.behavior.singleagent.planning.stochastic.montecarlo.uct.UCT
-
Performs a rollout in the UCT tree from the given node, keeping track of how many new nodes can be added to the tree.
- treeSize - Variable in class burlap.behavior.singleagent.planning.stochastic.montecarlo.uct.UCT
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- trialLength - Variable in class burlap.behavior.singleagent.auxiliary.performance.LearningAlgorithmExperimenter
-
The length of each trial
- trialLength - Variable in class burlap.behavior.stochasticgames.auxiliary.performance.MultiAgentExperimenter
-
The length of each trial
- trialLengthIsInEpisodes - Variable in class burlap.behavior.singleagent.auxiliary.performance.LearningAlgorithmExperimenter
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Whether the trial length specifies a number of episodes (which is the default) or the total number of steps
- trialLengthIsInEpisodes - Variable in class burlap.behavior.stochasticgames.auxiliary.performance.MultiAgentExperimenter
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Whether the trial length specifies a number of episodes (which is the default) or the total number of steps
- trialMode - Variable in class burlap.behavior.singleagent.auxiliary.performance.PerformancePlotter
-
specifies whether the most recent trial, average of all trials, or both plots will be displayed
- TrialMode - Enum in burlap.behavior.singleagent.auxiliary.performance
-
- trialMode - Variable in class burlap.behavior.stochasticgames.auxiliary.performance.MultiAgentPerformancePlotter
-
specifies whether the most recent trial, average of all trials, or both plots will be displayed
- trials - Variable in class burlap.behavior.stochasticgames.auxiliary.performance.MultiAgentPerformancePlotter.DatasetsAndTrials
-
All the trials with this agent
- trialUpdateComplete - Variable in class burlap.behavior.singleagent.auxiliary.performance.PerformancePlotter
-
Synchronization object to ensure proper threaded plot updating
- trialUpdateComplete - Variable in class burlap.behavior.stochasticgames.auxiliary.performance.MultiAgentPerformancePlotter
-
Synchronization object to ensure proper threaded plot updating
- tstreams - Variable in class burlap.oomdp.singleagent.explorer.VisualExplorer
-
- tstreams - Variable in class burlap.oomdp.stochasticgames.explorers.SGVisualExplorer
-
- type - Variable in class burlap.oomdp.core.Attribute
-
type of values attribute holds
- typeName - Variable in class burlap.oomdp.stochasticgames.SGAgentType
-