N-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

N

n - Variable in class burlap.behavior.singleagent.planning.stochastic.montecarlo.uct.UCTActionNode: The number of of times this action node has been taken
n - Variable in class burlap.behavior.singleagent.planning.stochastic.montecarlo.uct.UCTStateNode: The number of times this node has been visited
n - Variable in class burlap.mdp.stochasticgames.tournament.common.AllPairWiseSameTypeMS
name - Variable in class burlap.behavior.singleagent.options.MacroAction: The name of the action
name - Variable in class burlap.behavior.singleagent.options.SubgoalOption: The name of the option
name() - Method in class burlap.domain.singleagent.blockdude.state.BlockDudeAgent
name - Variable in class burlap.domain.singleagent.blockdude.state.BlockDudeCell
name() - Method in class burlap.domain.singleagent.blockdude.state.BlockDudeCell
name() - Method in class burlap.domain.singleagent.blockdude.state.BlockDudeMap
name - Variable in class burlap.domain.singleagent.blocksworld.BlocksWorld.NamedColor
name - Variable in class burlap.domain.singleagent.blocksworld.BlocksWorldBlock
name() - Method in class burlap.domain.singleagent.blocksworld.BlocksWorldBlock
name() - Method in class burlap.domain.singleagent.frostbite.state.FrostbiteAgent
name() - Method in class burlap.domain.singleagent.frostbite.state.FrostbiteIgloo
name - Variable in class burlap.domain.singleagent.frostbite.state.FrostbitePlatform
name() - Method in class burlap.domain.singleagent.frostbite.state.FrostbitePlatform
name - Variable in class burlap.domain.singleagent.gridworld.state.GridAgent
name() - Method in class burlap.domain.singleagent.gridworld.state.GridAgent
name - Variable in class burlap.domain.singleagent.gridworld.state.GridLocation
name() - Method in class burlap.domain.singleagent.gridworld.state.GridLocation
name() - Method in class burlap.domain.singleagent.lunarlander.state.LLAgent
name - Variable in class burlap.domain.singleagent.lunarlander.state.LLBlock
name() - Method in class burlap.domain.singleagent.lunarlander.state.LLBlock
name - Variable in class burlap.domain.stochasticgames.gridgame.state.GGAgent
name() - Method in class burlap.domain.stochasticgames.gridgame.state.GGAgent
name - Variable in class burlap.domain.stochasticgames.gridgame.state.GGGoal
name() - Method in class burlap.domain.stochasticgames.gridgame.state.GGGoal
name - Variable in class burlap.domain.stochasticgames.gridgame.state.GGWall
name() - Method in class burlap.domain.stochasticgames.gridgame.state.GGWall
name - Variable in class burlap.domain.stochasticgames.normalform.SingleStageNormalFormGame.MatrixAction
name - Variable in class burlap.mdp.core.action.SimpleAction
name - Variable in class burlap.mdp.core.oo.propositional.PropositionalFunction
name() - Method in interface burlap.mdp.core.oo.state.ObjectInstance: Returns the name of this object instance
name - Variable in class burlap.mdp.singleagent.oo.ObjectParameterizedActionType
name - Variable in class burlap.mdp.singleagent.oo.ObjectParameterizedActionType.SAObjectParameterizedAction
NamedColor() - Constructor for class burlap.domain.singleagent.blocksworld.BlocksWorld.NamedColor
NamedColor(String, Color) - Constructor for class burlap.domain.singleagent.blocksworld.BlocksWorld.NamedColor
namesToInd - Variable in class burlap.domain.stochasticgames.normalform.SingleStageNormalFormGame.ActionNameMap
nCols() - Method in class burlap.behavior.stochasticgames.agents.twoplayer.singlestage.equilibriumplayer.EquilibriumPlayingSGAgent.BimatrixTuple: Returns the number of columns
nConfident - Variable in class burlap.behavior.singleagent.learning.modellearning.models.TabularModel: The number of transitions necessary to be confident in a model's prediction.
needsClearing - Variable in class burlap.behavior.singleagent.auxiliary.performance.PerformancePlotter: Whether the current plots need their series data cleared for a new trial
needsClearing - Variable in class burlap.behavior.stochasticgames.auxiliary.performance.MultiAgentPerformancePlotter: Whether the current plots need their series data cleared for a new trial
needsToUpdateQValue - Variable in class burlap.behavior.stochasticgames.agents.maql.MultiAgentQLearning: Whether the agent needs to update its Q-values from a recent experience
needsUpdate - Variable in class burlap.datastructures.BoltzmannDistribution: Indicates whether the probabilities need to be recomputed
nextAction - Variable in class burlap.behavior.singleagent.interfaces.rlglue.RLGlueAgent: Maintains the current RLGlue action to be performed.
nextAction - Variable in class burlap.behavior.stochasticgames.agents.interfacing.singleagent.LearningAgentToSGAgentInterface: The next action selected by the single agent
nextAction - Variable in class burlap.shell.command.world.ManualAgentsCommands.ManualSGAgent
nextActionMultiplier - Variable in class burlap.behavior.functionapproximation.dense.fourier.FourierBasis: The next action Fourier basis function size multiplier to use for the next newly seen action.
nextActionMultiplier - Variable in class burlap.behavior.functionapproximation.dense.rbf.RBFFeatures: The next action RBF size multiplier to use for the next newly seen action.
nextEnumeratedID - Variable in class burlap.behavior.singleagent.auxiliary.StateEnumerator: The id to use for the next unique state that is added
nextFeatureId - Variable in class burlap.behavior.functionapproximation.sparse.SparseCrossProductFeatures
nextLRVal(double) - Method in class burlap.behavior.learningrate.ExponentialDecayLR: Returns the value of an input current learning rate after it has been decayed by one time step.
nextQValue - Variable in class burlap.behavior.stochasticgames.agents.maql.MultiAgentQLearning: The new Q-value to which the last Q-value needs to be udpated
nextState - Variable in class burlap.behavior.stochasticgames.agents.interfacing.singleagent.LearningAgentToSGAgentInterface: The next state received
nextStateFeatureId - Variable in class burlap.behavior.functionapproximation.sparse.tilecoding.TileCodingFeatures: The identifier to use for the next state feature.
nextStateReference - Variable in class burlap.behavior.singleagent.interfaces.rlglue.RLGlueAgent: Maintains the field to wait for the next state received from RLGlue
NFGameState - Class in burlap.domain.stochasticgames.normalform
NFGameState() - Constructor for class burlap.domain.stochasticgames.normalform.NFGameState: Default constructor for serialization
NFGameState(int) - Constructor for class burlap.domain.stochasticgames.normalform.NFGameState
NFGameState(String[]) - Constructor for class burlap.domain.stochasticgames.normalform.NFGameState
nodeComparator - Variable in class burlap.behavior.singleagent.planning.deterministic.informed.astar.IDAStar: The comparator to use for checking which nodes to expand first.
nodeMap - Variable in class burlap.datastructures.StochasticTree: A map from elements to the node that holds them.
nodesArray - Variable in class burlap.datastructures.HashIndexedHeap: Heap ordered list of objects
nodesByHeight - Variable in class burlap.behavior.singleagent.learnfromdemo.mlirl.differentiableplanners.DifferentiableSparseSampling: The tree nodes indexed by state and height.
nodesByHeight - Variable in class burlap.behavior.singleagent.planning.stochastic.sparsesampling.SparseSampling: The tree nodes indexed by state and height.
NodeTransitionProbability(int, double) - Constructor for class burlap.domain.singleagent.graphdefined.GraphDefinedDomain.NodeTransitionProbability: Initializes transition probability
NonMarkovOptionScanNode(State) - Constructor for class burlap.behavior.singleagent.options.model.BFSNonMarkovOptionModel.NonMarkovOptionScanNode
NonMarkovOptionScanNode(BFSNonMarkovOptionModel.NonMarkovOptionScanNode, State, double, double, Action) - Constructor for class burlap.behavior.singleagent.options.model.BFSNonMarkovOptionModel.NonMarkovOptionScanNode
nonZeroBeliefs() - Method in interface burlap.mdp.singleagent.pomdp.beliefstate.EnumerableBeliefState: Returns the states, and their probability mass, that have non-zero probability mass.
nonZeroBeliefs() - Method in class burlap.mdp.singleagent.pomdp.beliefstate.TabularBeliefState
norm(double) - Method in class burlap.mdp.core.state.vardomain.VariableDomain: Given a value in this variable domain, returns its normalized value.
NormalizedVariableFeatures - Class in burlap.behavior.functionapproximation.dense: This class is will construct a double array from states by iterating over numeric state variables and setting values in the double array to the variables normalized value.
NormalizedVariableFeatures() - Constructor for class burlap.behavior.functionapproximation.dense.NormalizedVariableFeatures
NormalizedVariableFeatures(Map<Object, VariableDomain>) - Constructor for class burlap.behavior.functionapproximation.dense.NormalizedVariableFeatures
normalRTDP(State) - Method in class burlap.behavior.singleagent.planning.stochastic.rtdp.RTDP: Runs normal RTDP in which bellman updates are performed after each action selection.
normSign - Variable in class burlap.domain.singleagent.cartpole.states.CartPoleFullState
nothing - Variable in class burlap.domain.singleagent.pomdp.tiger.TigerModel: The reward for do nothing.
nothingReward - Variable in class burlap.domain.singleagent.pomdp.tiger.TigerDomain: The reward for do nothing.
nPlayers - Variable in class burlap.domain.stochasticgames.normalform.SingleStageNormalFormGame: Number of players
nRbfs - Variable in class burlap.behavior.functionapproximation.dense.rbf.RBFFeatures: The number of RBF units, not including an offset unit.
nRows() - Method in class burlap.behavior.stochasticgames.agents.twoplayer.singlestage.equilibriumplayer.EquilibriumPlayingSGAgent.BimatrixTuple: Returns the number of rows
nSteps - Variable in class burlap.behavior.singleagent.options.model.BFSMarkovOptionModel.OptionScanNode: The number of steps taken to reach this node.
nTrials - Variable in class burlap.behavior.singleagent.auxiliary.performance.LearningAlgorithmExperimenter: The number of trials that each agent is evaluated
nTrials - Variable in class burlap.behavior.stochasticgames.auxiliary.performance.MultiAgentExperimenter: The number of trials that each agent is evaluted
NullHeuristic - Class in burlap.behavior.singleagent.planning.deterministic.informed: A Heuristic implementation that always returns 0.
NullHeuristic() - Constructor for class burlap.behavior.singleagent.planning.deterministic.informed.NullHeuristic
NullJointRewardFunction - Class in burlap.mdp.stochasticgames.common: A Joint reward function that always returns zero reward for each agent.
NullJointRewardFunction() - Constructor for class burlap.mdp.stochasticgames.common.NullJointRewardFunction
NullRewardFunction - Class in burlap.mdp.singleagent.common: This class defines a reward function that always returns 0
NullRewardFunction() - Constructor for class burlap.mdp.singleagent.common.NullRewardFunction
NullState - Class in burlap.mdp.core.state: A null state that contains no information.
NullTermination - Class in burlap.mdp.auxiliary.common: A terminal state function in which no state is considered a terminal state.
NullTermination() - Constructor for class burlap.mdp.auxiliary.common.NullTermination
numActions - Variable in class burlap.behavior.functionapproximation.dense.DenseCrossProductFeatures: The number of possible actions
numActions() - Method in class burlap.behavior.singleagent.Episode: Returns the number of actions, which is 1 less than the number of states.
numBellmanUpdates - Variable in class burlap.behavior.singleagent.planning.stochastic.rtdp.BoundedRTDP: Keeps track of the number of Bellman updates that have been performed across all planning.
numberOfBellmanUpdates - Variable in class burlap.behavior.singleagent.planning.stochastic.rtdp.RTDP: Stores the number of Bellman updates made across all planning.
numberPlatformCol - Variable in class burlap.domain.singleagent.frostbite.FrostbiteModel
numEMIterations - Variable in class burlap.behavior.singleagent.learnfromdemo.mlirl.MultipleIntentionsMLIRL: The number of EM iterations to run.
numEpisodesForPlanning - Variable in class burlap.behavior.singleagent.learning.actorcritic.ActorCritic: The number of simulated learning episodes to use when the ActorCritic.planFromState(State) method is called.
numEpisodesForPlanning - Variable in class burlap.behavior.singleagent.learning.tdmethods.QLearning: The maximum number of episodes to use for planning
numEpisodesForPlanning - Variable in class burlap.behavior.singleagent.learning.tdmethods.vfa.GradientDescentSarsaLam: The maximum number of episodes to use for planning
numEpisodesToStore - Variable in class burlap.behavior.singleagent.learning.actorcritic.ActorCritic: The number of most recent learning episodes to store.
numEpisodesToStore - Variable in class burlap.behavior.singleagent.learning.lspi.LSPI: The number of the most recent learning episodes to store.
numEpisodesToStore - Variable in class burlap.behavior.singleagent.learning.modellearning.artdp.ARTDP: The number of the most recent learning episodes to store.
numEpisodesToStore - Variable in class burlap.behavior.singleagent.learning.modellearning.rmax.PotentialShapedRMax: The number of the most recent learning episodes to store.
NumericVariableFeatures - Class in burlap.behavior.functionapproximation.dense: A DenseStateFeatures that iterates through all state variables in a state and places them into the returned double array.
NumericVariableFeatures() - Constructor for class burlap.behavior.functionapproximation.dense.NumericVariableFeatures
NumericVariableFeatures(Object...) - Constructor for class burlap.behavior.functionapproximation.dense.NumericVariableFeatures
NumericVariableFeatures(List<Object>) - Constructor for class burlap.behavior.functionapproximation.dense.NumericVariableFeatures
numFeatures() - Method in class burlap.behavior.functionapproximation.sparse.SparseCrossProductFeatures
numFeatures() - Method in interface burlap.behavior.functionapproximation.sparse.SparseStateActionFeatures: Returns the total number of features
numFeatures() - Method in interface burlap.behavior.functionapproximation.sparse.SparseStateFeatures: Returns the total number of features
numFeatures() - Method in class burlap.behavior.functionapproximation.sparse.tilecoding.TileCodingFeatures
numGames - Variable in class burlap.mdp.stochasticgames.tournament.Tournament
numGridPoints - Variable in class burlap.behavior.singleagent.auxiliary.gridset.VariableGridSpec: The number of grid points along this variable
numLocationTypes - Variable in class burlap.domain.singleagent.gridworld.GridWorldDomain: The number of possible location types
numNodes - Variable in class burlap.domain.singleagent.graphdefined.GraphDefinedDomain: The number of state nodes in the graph
numNonZeroPDs() - Method in interface burlap.behavior.functionapproximation.FunctionGradient: Returns the number of non-zero partial derivatives
numNonZeroPDs() - Method in class burlap.behavior.functionapproximation.FunctionGradient.SparseGradient
numObjects() - Method in class burlap.domain.singleagent.blockdude.state.BlockDudeState
numObjects() - Method in class burlap.domain.singleagent.blocksworld.BlocksWorldState
numObjects() - Method in class burlap.domain.singleagent.frostbite.state.FrostbiteState
numObjects() - Method in class burlap.domain.singleagent.gridworld.state.GridWorldState
numObjects() - Method in class burlap.domain.singleagent.lunarlander.state.LLState
numObjects() - Method in class burlap.mdp.core.oo.state.generic.GenericOOState
numObjects() - Method in interface burlap.mdp.core.oo.state.OOState: Returns the number of object instances in this state.
numOptionsInGAs(List<Action>) - Method in class burlap.behavior.singleagent.planning.deterministic.uninformed.dfs.DFS: Returns the number of options present in a list of possible actions.
numParameters() - Method in class burlap.behavior.functionapproximation.dense.DenseLinearVFA
numParameters() - Method in class burlap.behavior.functionapproximation.dense.DenseStateActionLinearVFA
numParameters() - Method in interface burlap.behavior.functionapproximation.ParametricFunction: Returns the number of parameters defining this function.
numParameters() - Method in class burlap.behavior.functionapproximation.sparse.LinearVFA
numParameters() - Method in class burlap.behavior.singleagent.learnfromdemo.mlirl.commonrfs.LinearStateActionDifferentiableRF
numParameters() - Method in class burlap.behavior.singleagent.learnfromdemo.mlirl.commonrfs.LinearStateDifferentiableRF
numParameters() - Method in class burlap.behavior.singleagent.learnfromdemo.mlirl.differentiableplanners.diffvinit.DiffVFRF
numParameters() - Method in class burlap.behavior.singleagent.learnfromdemo.mlirl.differentiableplanners.diffvinit.LinearDiffRFVInit
numParameters() - Method in class burlap.behavior.singleagent.learnfromdemo.mlirl.differentiableplanners.diffvinit.LinearStateDiffVF
numParameters() - Method in class burlap.behavior.singleagent.learnfromdemo.mlirl.differentiableplanners.diffvinit.VanillaDiffVinit
numRenderLayers() - Method in class burlap.visualizer.MultiLayerRenderer: Returns the number of render layers
numRollouts - Variable in class burlap.behavior.singleagent.planning.stochastic.rtdp.RTDP: the number of rollouts to perform when planning is started unless the value function delta is small enough.
numRollOutsFromRoot - Variable in class burlap.behavior.singleagent.planning.stochastic.montecarlo.uct.UCT
numSamplesForPlanning - Variable in class burlap.behavior.singleagent.learning.lspi.LSPI: the number of samples that are acquired for this object's dataset when the LSPI.planFromState(State) method is called.
numStateFeatures - Variable in class burlap.behavior.singleagent.learnfromdemo.mlirl.commonrfs.LinearStateActionDifferentiableRF: The number of state features
numStates() - Method in class burlap.mdp.singleagent.pomdp.beliefstate.TabularBeliefState: Returns the size of the observed underlying MDP state space.
numStatesEnumerated() - Method in class burlap.behavior.singleagent.auxiliary.StateEnumerator: Returns the number of states that have been enumerated
numStateVariables - Variable in class burlap.behavior.functionapproximation.dense.fourier.FourierBasis: The number of state variables on which the produced basis functions operate
numSteps() - Method in class burlap.behavior.singleagent.options.EnvironmentOptionOutcome
numSteps - Variable in class burlap.behavior.singleagent.planning.stochastic.rtdp.BoundedRTDP: Keeps track of the number of rollout steps that have been performed across all planning rollouts.
numStepsSinceLastLearningPI - Variable in class burlap.behavior.singleagent.learning.lspi.LSPI: Number of new observations received from learning episodes since LSPI was run
numTimeSteps() - Method in class burlap.behavior.singleagent.Episode: Returns the number of time steps in this episode, which is equivalent to the number of states.
numTimeSteps() - Method in class burlap.behavior.stochasticgames.GameEpisode: Returns the number of time steps recorded which is equal to the number of states observed.
numUpdates - Variable in class burlap.behavior.singleagent.learnfromdemo.mlirl.differentiableplanners.DifferentiableSparseSampling: The total number of pseudo-Bellman updates
numUpdates - Variable in class burlap.behavior.singleagent.planning.stochastic.sparsesampling.SparseSampling: The total number of pseudo-Bellman updates
numVisits - Variable in class burlap.behavior.singleagent.planning.stochastic.montecarlo.uct.UCT
numVisted - Variable in class burlap.behavior.singleagent.planning.deterministic.uninformed.dfs.DFS: Planning statistic for keeping track of how many nodes DFS expanded.
numXCells - Variable in class burlap.behavior.singleagent.auxiliary.valuefunctionvis.common.StateValuePainter2D: Option used for specifying the number of possible states that will be rendered in a row (i.e., across the x-axis).
numYCells - Variable in class burlap.behavior.singleagent.auxiliary.valuefunctionvis.common.StateValuePainter2D: Option used for specifying the number of possible states that will be rendered in a column (i.e., across the y-axis).

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