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

A

A3CConfiguration() - Constructor for class org.deeplearning4j.rl4j.learning.async.a3c.discrete.A3CDiscrete.A3CConfiguration

A3CDiscrete<O extends Encodable> - Class in org.deeplearning4j.rl4j.learning.async.a3c.discrete

A3CDiscrete(MDP<O, Integer, DiscreteSpace>, IActorCritic, A3CDiscrete.A3CConfiguration, IDataManager) - Constructor for class org.deeplearning4j.rl4j.learning.async.a3c.discrete.A3CDiscrete

A3CDiscrete.A3CConfiguration - Class in org.deeplearning4j.rl4j.learning.async.a3c.discrete

A3CDiscreteConv<O extends Encodable> - Class in org.deeplearning4j.rl4j.learning.async.a3c.discrete

A3CDiscreteConv(MDP<O, Integer, DiscreteSpace>, IActorCritic, IHistoryProcessor.Configuration, A3CDiscrete.A3CConfiguration, IDataManager) - Constructor for class org.deeplearning4j.rl4j.learning.async.a3c.discrete.A3CDiscreteConv

A3CDiscreteConv(MDP<O, Integer, DiscreteSpace>, ActorCriticFactoryCompGraph, IHistoryProcessor.Configuration, A3CDiscrete.A3CConfiguration, IDataManager) - Constructor for class org.deeplearning4j.rl4j.learning.async.a3c.discrete.A3CDiscreteConv

A3CDiscreteConv(MDP<O, Integer, DiscreteSpace>, ActorCriticFactoryCompGraphStdConv.Configuration, IHistoryProcessor.Configuration, A3CDiscrete.A3CConfiguration, IDataManager) - Constructor for class org.deeplearning4j.rl4j.learning.async.a3c.discrete.A3CDiscreteConv

A3CDiscreteDense<O extends Encodable> - Class in org.deeplearning4j.rl4j.learning.async.a3c.discrete

A3CDiscreteDense(MDP<O, Integer, DiscreteSpace>, IActorCritic, A3CDiscrete.A3CConfiguration, IDataManager) - Constructor for class org.deeplearning4j.rl4j.learning.async.a3c.discrete.A3CDiscreteDense

A3CDiscreteDense(MDP<O, Integer, DiscreteSpace>, ActorCriticFactorySeparate, A3CDiscrete.A3CConfiguration, IDataManager) - Constructor for class org.deeplearning4j.rl4j.learning.async.a3c.discrete.A3CDiscreteDense

A3CDiscreteDense(MDP<O, Integer, DiscreteSpace>, ActorCriticFactorySeparateStdDense.Configuration, A3CDiscrete.A3CConfiguration, IDataManager) - Constructor for class org.deeplearning4j.rl4j.learning.async.a3c.discrete.A3CDiscreteDense

A3CDiscreteDense(MDP<O, Integer, DiscreteSpace>, ActorCriticFactoryCompGraph, A3CDiscrete.A3CConfiguration, IDataManager) - Constructor for class org.deeplearning4j.rl4j.learning.async.a3c.discrete.A3CDiscreteDense

A3CDiscreteDense(MDP<O, Integer, DiscreteSpace>, ActorCriticFactoryCompGraphStdDense.Configuration, A3CDiscrete.A3CConfiguration, IDataManager) - Constructor for class org.deeplearning4j.rl4j.learning.async.a3c.discrete.A3CDiscreteDense

A3CThreadDiscrete<O extends Encodable> - Class in org.deeplearning4j.rl4j.learning.async.a3c.discrete

A3CThreadDiscrete(MDP<O, Integer, DiscreteSpace>, AsyncGlobal<IActorCritic>, A3CDiscrete.A3CConfiguration, int, IDataManager, int) - Constructor for class org.deeplearning4j.rl4j.learning.async.a3c.discrete.A3CThreadDiscrete

ACPolicy<O extends Encodable> - Class in org.deeplearning4j.rl4j.policy

ACPolicy(IActorCritic) - Constructor for class org.deeplearning4j.rl4j.policy.ACPolicy

ACPolicy(IActorCritic, Random) - Constructor for class org.deeplearning4j.rl4j.policy.ACPolicy

ActorCriticCompGraph<NN extends ActorCriticCompGraph> - Class in org.deeplearning4j.rl4j.network.ac

ActorCriticCompGraph(ComputationGraph) - Constructor for class org.deeplearning4j.rl4j.network.ac.ActorCriticCompGraph

ActorCriticFactoryCompGraph - Interface in org.deeplearning4j.rl4j.network.ac

ActorCriticFactoryCompGraphStdConv - Class in org.deeplearning4j.rl4j.network.ac

ActorCriticFactoryCompGraphStdConv() - Constructor for class org.deeplearning4j.rl4j.network.ac.ActorCriticFactoryCompGraphStdConv

ActorCriticFactoryCompGraphStdConv.Configuration - Class in org.deeplearning4j.rl4j.network.ac

ActorCriticFactoryCompGraphStdDense - Class in org.deeplearning4j.rl4j.network.ac

ActorCriticFactoryCompGraphStdDense() - Constructor for class org.deeplearning4j.rl4j.network.ac.ActorCriticFactoryCompGraphStdDense

ActorCriticFactoryCompGraphStdDense.Configuration - Class in org.deeplearning4j.rl4j.network.ac

ActorCriticFactorySeparate - Interface in org.deeplearning4j.rl4j.network.ac

ActorCriticFactorySeparateStdDense - Class in org.deeplearning4j.rl4j.network.ac

ActorCriticFactorySeparateStdDense() - Constructor for class org.deeplearning4j.rl4j.network.ac.ActorCriticFactorySeparateStdDense

ActorCriticFactorySeparateStdDense.Configuration - Class in org.deeplearning4j.rl4j.network.ac

ActorCriticLoss - Class in org.deeplearning4j.rl4j.network.ac

Custom loss function required for Actor-Critic methods:

ActorCriticLoss() - Constructor for class org.deeplearning4j.rl4j.network.ac.ActorCriticLoss

ActorCriticSeparate<NN extends ActorCriticSeparate> - Class in org.deeplearning4j.rl4j.network.ac

ActorCriticSeparate(MultiLayerNetwork, MultiLayerNetwork) - Constructor for class org.deeplearning4j.rl4j.network.ac.ActorCriticSeparate

add(INDArray) - Method in class org.deeplearning4j.rl4j.learning.HistoryProcessor

add(INDArray) - Method in interface org.deeplearning4j.rl4j.learning.IHistoryProcessor

add(INDArray) - Method in class org.deeplearning4j.rl4j.observation.preprocessor.pooling.CircularFifoObservationPool

Add an element to the pool, if this addition would make the pool to overflow, the added element replaces the oldest one.

add(INDArray) - Method in interface org.deeplearning4j.rl4j.observation.preprocessor.pooling.ObservationPool

addListener(SyncTrainingListener) - Method in class org.deeplearning4j.rl4j.learning.sync.SyncLearning

Add a listener at the end of the listener list.

append(INDArray[], INDArray) - Static method in class org.deeplearning4j.rl4j.learning.sync.Transition

append a pixel frame to an history (throwing the last frame)

appendStat(IDataManager.StatEntry) - Method in class org.deeplearning4j.rl4j.util.DataManager

appendStat(IDataManager.StatEntry) - Method in interface org.deeplearning4j.rl4j.util.IDataManager

applyGradient(Gradient[], int) - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticCompGraph

applyGradient(Gradient[], int) - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticSeparate

applyGradient(Gradient[], int) - Method in interface org.deeplearning4j.rl4j.network.ac.IActorCritic

applyGradient(Gradient[], int) - Method in class org.deeplearning4j.rl4j.network.dqn.DQN

applyGradient(Gradient[], int) - Method in interface org.deeplearning4j.rl4j.network.dqn.IDQN

applyGradient(Gradient[], int) - Method in interface org.deeplearning4j.rl4j.network.NeuralNet

update the params from the gradients and the batchSize

assemble(INDArray[]) - Method in class org.deeplearning4j.rl4j.observation.preprocessor.pooling.ChannelStackPoolContentAssembler

Will return a new INDArray with one more dimension and with poolContent stacked along dimension 0.

assemble(INDArray[]) - Method in interface org.deeplearning4j.rl4j.observation.preprocessor.pooling.PoolContentAssembler

AsyncConfiguration - Interface in org.deeplearning4j.rl4j.learning.async

asyncGlobal - Variable in class org.deeplearning4j.rl4j.learning.async.a3c.discrete.A3CThreadDiscrete

AsyncGlobal<NN extends NeuralNet> - Class in org.deeplearning4j.rl4j.learning.async

AsyncGlobal(NN, AsyncConfiguration) - Constructor for class org.deeplearning4j.rl4j.learning.async.AsyncGlobal

asyncGlobal - Variable in class org.deeplearning4j.rl4j.learning.async.nstep.discrete.AsyncNStepQLearningThreadDiscrete

AsyncLearning<O extends Encodable,A,AS extends ActionSpace<A>,NN extends NeuralNet> - Class in org.deeplearning4j.rl4j.learning.async

AsyncLearning(AsyncConfiguration) - Constructor for class org.deeplearning4j.rl4j.learning.async.AsyncLearning

AsyncNStepQLConfiguration() - Constructor for class org.deeplearning4j.rl4j.learning.async.nstep.discrete.AsyncNStepQLearningDiscrete.AsyncNStepQLConfiguration

AsyncNStepQLearningDiscrete<O extends Encodable> - Class in org.deeplearning4j.rl4j.learning.async.nstep.discrete

AsyncNStepQLearningDiscrete(MDP<O, Integer, DiscreteSpace>, IDQN, AsyncNStepQLearningDiscrete.AsyncNStepQLConfiguration, IDataManager) - Constructor for class org.deeplearning4j.rl4j.learning.async.nstep.discrete.AsyncNStepQLearningDiscrete

AsyncNStepQLearningDiscrete.AsyncNStepQLConfiguration - Class in org.deeplearning4j.rl4j.learning.async.nstep.discrete

AsyncNStepQLearningDiscreteConv<O extends Encodable> - Class in org.deeplearning4j.rl4j.learning.async.nstep.discrete

AsyncNStepQLearningDiscreteConv(MDP<O, Integer, DiscreteSpace>, IDQN, IHistoryProcessor.Configuration, AsyncNStepQLearningDiscrete.AsyncNStepQLConfiguration, IDataManager) - Constructor for class org.deeplearning4j.rl4j.learning.async.nstep.discrete.AsyncNStepQLearningDiscreteConv

AsyncNStepQLearningDiscreteConv(MDP<O, Integer, DiscreteSpace>, DQNFactory, IHistoryProcessor.Configuration, AsyncNStepQLearningDiscrete.AsyncNStepQLConfiguration, IDataManager) - Constructor for class org.deeplearning4j.rl4j.learning.async.nstep.discrete.AsyncNStepQLearningDiscreteConv

AsyncNStepQLearningDiscreteConv(MDP<O, Integer, DiscreteSpace>, DQNFactoryStdConv.Configuration, IHistoryProcessor.Configuration, AsyncNStepQLearningDiscrete.AsyncNStepQLConfiguration, IDataManager) - Constructor for class org.deeplearning4j.rl4j.learning.async.nstep.discrete.AsyncNStepQLearningDiscreteConv

AsyncNStepQLearningDiscreteDense<O extends Encodable> - Class in org.deeplearning4j.rl4j.learning.async.nstep.discrete

AsyncNStepQLearningDiscreteDense(MDP<O, Integer, DiscreteSpace>, IDQN, AsyncNStepQLearningDiscrete.AsyncNStepQLConfiguration, IDataManager) - Constructor for class org.deeplearning4j.rl4j.learning.async.nstep.discrete.AsyncNStepQLearningDiscreteDense

AsyncNStepQLearningDiscreteDense(MDP<O, Integer, DiscreteSpace>, DQNFactory, AsyncNStepQLearningDiscrete.AsyncNStepQLConfiguration, IDataManager) - Constructor for class org.deeplearning4j.rl4j.learning.async.nstep.discrete.AsyncNStepQLearningDiscreteDense

AsyncNStepQLearningDiscreteDense(MDP<O, Integer, DiscreteSpace>, DQNFactoryStdDense.Configuration, AsyncNStepQLearningDiscrete.AsyncNStepQLConfiguration, IDataManager) - Constructor for class org.deeplearning4j.rl4j.learning.async.nstep.discrete.AsyncNStepQLearningDiscreteDense

AsyncNStepQLearningThreadDiscrete<O extends Encodable> - Class in org.deeplearning4j.rl4j.learning.async.nstep.discrete

AsyncNStepQLearningThreadDiscrete(MDP<O, Integer, DiscreteSpace>, IAsyncGlobal<IDQN>, AsyncNStepQLearningDiscrete.AsyncNStepQLConfiguration, int, IDataManager, int) - Constructor for class org.deeplearning4j.rl4j.learning.async.nstep.discrete.AsyncNStepQLearningThreadDiscrete

AsyncStatEntry() - Constructor for class org.deeplearning4j.rl4j.learning.async.AsyncThread.AsyncStatEntry

AsyncThread<O extends Encodable,A,AS extends ActionSpace<A>,NN extends NeuralNet> - Class in org.deeplearning4j.rl4j.learning.async

AsyncThread(IAsyncGlobal<NN>, int, int) - Constructor for class org.deeplearning4j.rl4j.learning.async.AsyncThread

AsyncThread.AsyncStatEntry - Class in org.deeplearning4j.rl4j.learning.async

AsyncThread.SubEpochReturn<O> - Class in org.deeplearning4j.rl4j.learning.async

AsyncThreadDiscrete<O extends Encodable,NN extends NeuralNet> - Class in org.deeplearning4j.rl4j.learning.async

AsyncThreadDiscrete(IAsyncGlobal<NN>, int, int) - Constructor for class org.deeplearning4j.rl4j.learning.async.AsyncThreadDiscrete

B

BETA - Static variable in class org.deeplearning4j.rl4j.network.ac.ActorCriticLoss

BoltzmannQ<O extends Encodable> - Class in org.deeplearning4j.rl4j.policy

BoltzmannQ() - Constructor for class org.deeplearning4j.rl4j.policy.BoltzmannQ

build() - Method in class org.deeplearning4j.rl4j.observation.preprocessor.pooling.CircularFifoObservationPool.Builder

build() - Method in class org.deeplearning4j.rl4j.observation.preprocessor.PoolingDataSetPreProcessor.Builder

build() - Method in class org.deeplearning4j.rl4j.util.DataManagerSyncTrainingListener.Builder

Creates a DataManagerSyncTrainingListener with the configured parameters

buildActorCritic(int[], int) - Method in interface org.deeplearning4j.rl4j.network.ac.ActorCriticFactoryCompGraph

buildActorCritic(int[], int) - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticFactoryCompGraphStdConv

buildActorCritic(int[], int) - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticFactoryCompGraphStdDense

buildActorCritic(int[], int) - Method in interface org.deeplearning4j.rl4j.network.ac.ActorCriticFactorySeparate

buildActorCritic(int[], int) - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticFactorySeparateStdDense

buildDQN(int[], int) - Method in interface org.deeplearning4j.rl4j.network.dqn.DQNFactory

buildDQN(int[], int) - Method in class org.deeplearning4j.rl4j.network.dqn.DQNFactoryStdConv

buildDQN(int[], int) - Method in class org.deeplearning4j.rl4j.network.dqn.DQNFactoryStdDense

builder() - Static method in class org.deeplearning4j.rl4j.observation.preprocessor.pooling.CircularFifoObservationPool

Builder() - Constructor for class org.deeplearning4j.rl4j.observation.preprocessor.pooling.CircularFifoObservationPool.Builder

builder() - Static method in class org.deeplearning4j.rl4j.observation.preprocessor.PoolingDataSetPreProcessor

Builder() - Constructor for class org.deeplearning4j.rl4j.observation.preprocessor.PoolingDataSetPreProcessor.Builder

builder(IDataManager) - Static method in class org.deeplearning4j.rl4j.util.DataManagerSyncTrainingListener

Builder(IDataManager) - Constructor for class org.deeplearning4j.rl4j.util.DataManagerSyncTrainingListener.Builder

Create a Builder with the given DataManager

C

calcGradient(IActorCritic, Stack<MiniTrans<Integer>>) - Method in class org.deeplearning4j.rl4j.learning.async.a3c.discrete.A3CThreadDiscrete

calc the gradients based on the n-step rewards

calcGradient(NN, Stack<MiniTrans<Integer>>) - Method in class org.deeplearning4j.rl4j.learning.async.AsyncThreadDiscrete

calcGradient(IDQN, Stack<MiniTrans<Integer>>) - Method in class org.deeplearning4j.rl4j.learning.async.nstep.discrete.AsyncNStepQLearningThreadDiscrete

cg - Variable in class org.deeplearning4j.rl4j.network.ac.ActorCriticCompGraph

ChannelStackPoolContentAssembler - Class in org.deeplearning4j.rl4j.observation.preprocessor.pooling

ChannelStackPoolContentAssembler is used with the PoolingDataSetPreProcessor.

ChannelStackPoolContentAssembler() - Constructor for class org.deeplearning4j.rl4j.observation.preprocessor.pooling.ChannelStackPoolContentAssembler

CircularFifoObservationPool - Class in org.deeplearning4j.rl4j.observation.preprocessor.pooling

CircularFifoObservationPool is used with the PoolingDataSetPreProcessor.

CircularFifoObservationPool() - Constructor for class org.deeplearning4j.rl4j.observation.preprocessor.pooling.CircularFifoObservationPool

CircularFifoObservationPool(int) - Constructor for class org.deeplearning4j.rl4j.observation.preprocessor.pooling.CircularFifoObservationPool

CircularFifoObservationPool.Builder - Class in org.deeplearning4j.rl4j.observation.preprocessor.pooling

clone() - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticCompGraph

clone() - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticSeparate

clone() - Method in interface org.deeplearning4j.rl4j.network.ac.IActorCritic

clone() - Method in class org.deeplearning4j.rl4j.network.dqn.DQN

clone() - Method in interface org.deeplearning4j.rl4j.network.dqn.IDQN

clone() - Method in interface org.deeplearning4j.rl4j.network.NeuralNet

clone the Neural Net with the same paramaeters

close() - Method in class org.deeplearning4j.rl4j.mdp.toy.HardDeteministicToy

close() - Method in class org.deeplearning4j.rl4j.mdp.toy.SimpleToy

computeGradient(INDArray, INDArray, IActivation, INDArray) - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticLoss

computeGradientAndScore(INDArray, INDArray, IActivation, INDArray, boolean) - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticLoss

computeScore(INDArray, INDArray, IActivation, INDArray, boolean) - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticLoss

computeScoreArray(INDArray, INDArray, IActivation, INDArray) - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticLoss

concat(INDArray[]) - Static method in class org.deeplearning4j.rl4j.learning.sync.Transition

concat an array history into a single INDArry of as many channel as element in the history array

conf - Variable in class org.deeplearning4j.rl4j.learning.async.a3c.discrete.A3CThreadDiscrete

conf - Variable in class org.deeplearning4j.rl4j.learning.async.nstep.discrete.AsyncNStepQLearningThreadDiscrete

configuration - Variable in class org.deeplearning4j.rl4j.learning.async.a3c.discrete.A3CDiscrete

configuration - Variable in class org.deeplearning4j.rl4j.learning.async.nstep.discrete.AsyncNStepQLearningDiscrete

Configuration() - Constructor for class org.deeplearning4j.rl4j.learning.IHistoryProcessor.Configuration

Configuration() - Constructor for class org.deeplearning4j.rl4j.network.ac.ActorCriticFactoryCompGraphStdConv.Configuration

Configuration() - Constructor for class org.deeplearning4j.rl4j.network.ac.ActorCriticFactoryCompGraphStdDense.Configuration

Configuration() - Constructor for class org.deeplearning4j.rl4j.network.ac.ActorCriticFactorySeparateStdDense.Configuration

Configuration() - Constructor for class org.deeplearning4j.rl4j.network.dqn.DQNFactoryStdConv.Configuration

Configuration() - Constructor for class org.deeplearning4j.rl4j.network.dqn.DQNFactoryStdDense.Configuration

Constants - Class in org.deeplearning4j.rl4j.util

Constants() - Constructor for class org.deeplearning4j.rl4j.util.Constants

copy(NN) - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticCompGraph

copy(NN) - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticSeparate

copy(NN) - Method in interface org.deeplearning4j.rl4j.network.ac.IActorCritic

copy(NN) - Method in class org.deeplearning4j.rl4j.network.dqn.DQN

copy(NN) - Method in interface org.deeplearning4j.rl4j.network.dqn.IDQN

copy(NN) - Method in interface org.deeplearning4j.rl4j.network.NeuralNet

copy the parameters from a neural net

createSubdir() - Method in class org.deeplearning4j.rl4j.util.DataManager

D

DATA_DIR - Static variable in class org.deeplearning4j.rl4j.util.Constants

dataManager - Variable in class org.deeplearning4j.rl4j.learning.async.a3c.discrete.A3CThreadDiscrete

dataManager - Variable in class org.deeplearning4j.rl4j.learning.async.nstep.discrete.AsyncNStepQLearningThreadDiscrete

DataManager - Class in org.deeplearning4j.rl4j.util

DataManager() - Constructor for class org.deeplearning4j.rl4j.util.DataManager

DataManager(boolean) - Constructor for class org.deeplearning4j.rl4j.util.DataManager

DataManager(String, boolean) - Constructor for class org.deeplearning4j.rl4j.util.DataManager

DataManager.Info - Class in org.deeplearning4j.rl4j.util

DataManagerSyncTrainingListener - Class in org.deeplearning4j.rl4j.util

DataManagerSyncTrainingListener can be added to the listeners of SyncLearning so that the training process can be fed to the DataManager

DataManagerSyncTrainingListener.Builder - Class in org.deeplearning4j.rl4j.util

deviceNum - Variable in class org.deeplearning4j.rl4j.learning.async.AsyncThread

DQN<NN extends DQN> - Class in org.deeplearning4j.rl4j.network.dqn

DQN(MultiLayerNetwork) - Constructor for class org.deeplearning4j.rl4j.network.dqn.DQN

DQNFactory - Interface in org.deeplearning4j.rl4j.network.dqn

DQNFactoryStdConv - Class in org.deeplearning4j.rl4j.network.dqn

DQNFactoryStdConv() - Constructor for class org.deeplearning4j.rl4j.network.dqn.DQNFactoryStdConv

DQNFactoryStdConv.Configuration - Class in org.deeplearning4j.rl4j.network.dqn

DQNFactoryStdDense - Class in org.deeplearning4j.rl4j.network.dqn

DQNFactoryStdDense() - Constructor for class org.deeplearning4j.rl4j.network.dqn.DQNFactoryStdDense

DQNFactoryStdDense.Configuration - Class in org.deeplearning4j.rl4j.network.dqn

dqnOutput(INDArray) - Method in class org.deeplearning4j.rl4j.learning.sync.qlearning.QLearning

DQNPolicy<O extends Encodable> - Class in org.deeplearning4j.rl4j.policy

DQNPolicy() - Constructor for class org.deeplearning4j.rl4j.policy.DQNPolicy

dup() - Method in class org.deeplearning4j.rl4j.learning.sync.Transition

Duplicate this transition

dup(INDArray[]) - Static method in class org.deeplearning4j.rl4j.learning.sync.Transition

Duplicate an history

E

enqueue(Gradient[], Integer) - Method in class org.deeplearning4j.rl4j.learning.async.AsyncGlobal

enqueue(Gradient[], Integer) - Method in interface org.deeplearning4j.rl4j.learning.async.IAsyncGlobal

EpsGreedy<O extends Encodable,A,AS extends ActionSpace<A>> - Class in org.deeplearning4j.rl4j.policy

EpsGreedy() - Constructor for class org.deeplearning4j.rl4j.policy.EpsGreedy

ExpReplay<A> - Class in org.deeplearning4j.rl4j.learning.sync

ExpReplay(int, int, int) - Constructor for class org.deeplearning4j.rl4j.learning.sync.ExpReplay

expReplay - Variable in class org.deeplearning4j.rl4j.learning.sync.qlearning.QLearning

F

fit(INDArray, INDArray[]) - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticCompGraph

fit(INDArray, INDArray[]) - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticSeparate

fit(INDArray, INDArray[]) - Method in interface org.deeplearning4j.rl4j.network.ac.IActorCritic

fit(INDArray, INDArray) - Method in class org.deeplearning4j.rl4j.network.dqn.DQN

fit(INDArray, INDArray[]) - Method in class org.deeplearning4j.rl4j.network.dqn.DQN

fit(INDArray, INDArray) - Method in interface org.deeplearning4j.rl4j.network.dqn.IDQN

fit(INDArray, INDArray[]) - Method in interface org.deeplearning4j.rl4j.network.dqn.IDQN

fit(INDArray, INDArray[]) - Method in interface org.deeplearning4j.rl4j.network.NeuralNet

fit from input and labels

G

genToyStates(int, int) - Static method in class org.deeplearning4j.rl4j.mdp.toy.HardDeteministicToy

get() - Method in class org.deeplearning4j.rl4j.observation.preprocessor.pooling.CircularFifoObservationPool

get() - Method in interface org.deeplearning4j.rl4j.observation.preprocessor.pooling.ObservationPool

getAsyncGlobal() - Method in class org.deeplearning4j.rl4j.learning.async.AsyncLearning

getAsyncGlobal() - Method in class org.deeplearning4j.rl4j.learning.async.AsyncThread

getBatch(int) - Method in class org.deeplearning4j.rl4j.learning.sync.ExpReplay

getBatch() - Method in class org.deeplearning4j.rl4j.learning.sync.ExpReplay

getBatch() - Method in interface org.deeplearning4j.rl4j.learning.sync.IExpReplay

getConf() - Method in class org.deeplearning4j.rl4j.learning.async.AsyncThread

getConf() - Method in interface org.deeplearning4j.rl4j.learning.IHistoryProcessor

getConfiguration() - Method in class org.deeplearning4j.rl4j.learning.async.AsyncLearning

getConfiguration() - Method in interface org.deeplearning4j.rl4j.learning.ILearning

getConfiguration() - Method in class org.deeplearning4j.rl4j.learning.sync.qlearning.QLearning

getCurrent() - Method in class org.deeplearning4j.rl4j.learning.async.AsyncThread

getCurrent() - Method in interface org.deeplearning4j.rl4j.learning.async.IAsyncGlobal

getCurrentDQN() - Method in class org.deeplearning4j.rl4j.learning.sync.qlearning.QLearning

getDataManager() - Method in class org.deeplearning4j.rl4j.learning.async.AsyncLearning

getDataManager() - Method in class org.deeplearning4j.rl4j.learning.async.AsyncThread

getEgPolicy() - Method in class org.deeplearning4j.rl4j.learning.sync.qlearning.QLearning

getEpochCounter() - Method in interface org.deeplearning4j.rl4j.util.IDataManager.StatEntry

getEpsilon() - Method in class org.deeplearning4j.rl4j.policy.EpsGreedy

getErrorClamp() - Method in interface org.deeplearning4j.rl4j.learning.async.AsyncConfiguration

getGamma() - Method in interface org.deeplearning4j.rl4j.learning.async.AsyncConfiguration

getGamma() - Method in interface org.deeplearning4j.rl4j.learning.ILearning.LConfiguration

getHistory() - Method in class org.deeplearning4j.rl4j.learning.HistoryProcessor

getHistory() - Method in interface org.deeplearning4j.rl4j.learning.IHistoryProcessor

Returns compressed arrays, which must be rescaled based on the value returned by IHistoryProcessor.getScale().

getInfo() - Method in class org.deeplearning4j.rl4j.util.DataManager

getInput(MDP<O, A, AS>, O) - Static method in class org.deeplearning4j.rl4j.learning.Learning

getInput(O) - Method in class org.deeplearning4j.rl4j.learning.Learning

getLatestScore() - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticCompGraph

getLatestScore() - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticSeparate

getLatestScore() - Method in interface org.deeplearning4j.rl4j.network.ac.IActorCritic

getLatestScore() - Method in class org.deeplearning4j.rl4j.network.dqn.DQN

getLatestScore() - Method in interface org.deeplearning4j.rl4j.network.dqn.IDQN

getLatestScore() - Method in interface org.deeplearning4j.rl4j.network.NeuralNet

latest score from lastest fit

getMaxAction(INDArray) - Static method in class org.deeplearning4j.rl4j.learning.Learning

getMaxEpochStep() - Method in interface org.deeplearning4j.rl4j.learning.async.AsyncConfiguration

getMaxEpochStep() - Method in interface org.deeplearning4j.rl4j.learning.ILearning.LConfiguration

getMaxStep() - Method in interface org.deeplearning4j.rl4j.learning.async.AsyncConfiguration

getMaxStep() - Method in interface org.deeplearning4j.rl4j.learning.ILearning.LConfiguration

getMdp() - Method in class org.deeplearning4j.rl4j.learning.async.AsyncThread

getMdp() - Method in interface org.deeplearning4j.rl4j.learning.ILearning

getMdp() - Method in class org.deeplearning4j.rl4j.learning.sync.qlearning.QLearning

getModelDir() - Method in class org.deeplearning4j.rl4j.util.DataManager

getNeuralNet() - Method in class org.deeplearning4j.rl4j.learning.async.a3c.discrete.A3CDiscrete

getNeuralNet() - Method in class org.deeplearning4j.rl4j.learning.async.nstep.discrete.AsyncNStepQLearningDiscrete

getNeuralNet() - Method in class org.deeplearning4j.rl4j.learning.Learning

getNeuralNet() - Method in interface org.deeplearning4j.rl4j.learning.NeuralNetFetchable

getNeuralNet() - Method in class org.deeplearning4j.rl4j.learning.sync.qlearning.QLearning

getNeuralNet() - Method in class org.deeplearning4j.rl4j.policy.ACPolicy

getNeuralNet() - Method in class org.deeplearning4j.rl4j.policy.BoltzmannQ

getNeuralNet() - Method in class org.deeplearning4j.rl4j.policy.DQNPolicy

getNeuralNet() - Method in class org.deeplearning4j.rl4j.policy.EpsGreedy

getNeuralNet() - Method in class org.deeplearning4j.rl4j.policy.Policy

getNeuralNetworks() - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticCompGraph

getNeuralNetworks() - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticSeparate

getNeuralNetworks() - Method in class org.deeplearning4j.rl4j.network.dqn.DQN

getNeuralNetworks() - Method in interface org.deeplearning4j.rl4j.network.NeuralNet

Returns the underlying MultiLayerNetwork or ComputationGraph objects.

getNstep() - Method in interface org.deeplearning4j.rl4j.learning.async.AsyncConfiguration

getNumThread() - Method in interface org.deeplearning4j.rl4j.learning.async.AsyncConfiguration

getPolicy(IActorCritic) - Method in class org.deeplearning4j.rl4j.learning.async.a3c.discrete.A3CThreadDiscrete

getPolicy(NN) - Method in class org.deeplearning4j.rl4j.learning.async.AsyncThread

getPolicy() - Method in class org.deeplearning4j.rl4j.learning.async.nstep.discrete.AsyncNStepQLearningDiscrete

getPolicy(IDQN) - Method in class org.deeplearning4j.rl4j.learning.async.nstep.discrete.AsyncNStepQLearningThreadDiscrete

getPolicy() - Method in interface org.deeplearning4j.rl4j.learning.ILearning

getReward() - Method in interface org.deeplearning4j.rl4j.util.IDataManager.StatEntry

getRewardFactor() - Method in interface org.deeplearning4j.rl4j.learning.async.AsyncConfiguration

getScale() - Method in class org.deeplearning4j.rl4j.learning.HistoryProcessor

getScale() - Method in interface org.deeplearning4j.rl4j.learning.IHistoryProcessor

Returns the scale of the arrays returned by IHistoryProcessor.getHistory(), typically 255.

getSeed() - Method in interface org.deeplearning4j.rl4j.learning.async.AsyncConfiguration

getSeed() - Method in interface org.deeplearning4j.rl4j.learning.ILearning.LConfiguration

getShape() - Method in class org.deeplearning4j.rl4j.learning.IHistoryProcessor.Configuration

getStat() - Method in class org.deeplearning4j.rl4j.util.DataManager

getStepCounter() - Method in class org.deeplearning4j.rl4j.learning.async.AsyncLearning

getStepCounter() - Method in interface org.deeplearning4j.rl4j.learning.ILearning

getStepCounter() - Method in interface org.deeplearning4j.rl4j.learning.StepCountable

getStepCounter() - Method in interface org.deeplearning4j.rl4j.util.IDataManager.StatEntry

getT() - Method in interface org.deeplearning4j.rl4j.learning.async.IAsyncGlobal

getTarget() - Method in interface org.deeplearning4j.rl4j.learning.async.IAsyncGlobal

getTargetDQN() - Method in class org.deeplearning4j.rl4j.learning.sync.qlearning.QLearning

getTargetDqnUpdateFreq() - Method in class org.deeplearning4j.rl4j.learning.async.a3c.discrete.A3CDiscrete.A3CConfiguration

getTargetDqnUpdateFreq() - Method in interface org.deeplearning4j.rl4j.learning.async.AsyncConfiguration

getThreadNumber() - Method in class org.deeplearning4j.rl4j.learning.async.AsyncThread

getUpdateStart() - Method in interface org.deeplearning4j.rl4j.learning.async.AsyncConfiguration

getVideoDir() - Method in class org.deeplearning4j.rl4j.util.DataManager

getVideoDir() - Method in interface org.deeplearning4j.rl4j.util.IDataManager

gradient(INDArray, INDArray[]) - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticCompGraph

gradient(INDArray, INDArray[]) - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticSeparate

gradient(INDArray, INDArray[]) - Method in interface org.deeplearning4j.rl4j.network.ac.IActorCritic

gradient(INDArray, INDArray) - Method in class org.deeplearning4j.rl4j.network.dqn.DQN

gradient(INDArray, INDArray[]) - Method in class org.deeplearning4j.rl4j.network.dqn.DQN

gradient(INDArray, INDArray) - Method in interface org.deeplearning4j.rl4j.network.dqn.IDQN

gradient(INDArray, INDArray[]) - Method in interface org.deeplearning4j.rl4j.network.dqn.IDQN

gradient(INDArray, INDArray[]) - Method in interface org.deeplearning4j.rl4j.network.NeuralNet

Calculate the gradients from input and label (target) of all outputs

H

HardDeteministicToy - Class in org.deeplearning4j.rl4j.mdp.toy

HardDeteministicToy() - Constructor for class org.deeplearning4j.rl4j.mdp.toy.HardDeteministicToy

HardToyState - Class in org.deeplearning4j.rl4j.mdp.toy

HardToyState() - Constructor for class org.deeplearning4j.rl4j.mdp.toy.HardToyState

HistoryProcessor - Class in org.deeplearning4j.rl4j.learning

HistoryProcessor(IHistoryProcessor.Configuration) - Constructor for class org.deeplearning4j.rl4j.learning.HistoryProcessor

I

IActorCritic<NN extends IActorCritic> - Interface in org.deeplearning4j.rl4j.network.ac

IAsyncGlobal<NN extends NeuralNet> - Interface in org.deeplearning4j.rl4j.learning.async

IDataManager - Interface in org.deeplearning4j.rl4j.util

IDataManager.StatEntry - Interface in org.deeplearning4j.rl4j.util

IDQN<NN extends IDQN> - Interface in org.deeplearning4j.rl4j.network.dqn

IExpReplay<A> - Interface in org.deeplearning4j.rl4j.learning.sync

IHistoryProcessor - Interface in org.deeplearning4j.rl4j.learning

IHistoryProcessor.Configuration - Class in org.deeplearning4j.rl4j.learning

ILearning<O extends Encodable,A,AS extends ActionSpace<A>> - Interface in org.deeplearning4j.rl4j.learning

ILearning.LConfiguration - Interface in org.deeplearning4j.rl4j.learning

incrementEpoch() - Method in class org.deeplearning4j.rl4j.learning.Learning

incrementStep() - Method in class org.deeplearning4j.rl4j.learning.Learning

Info() - Constructor for class org.deeplearning4j.rl4j.util.DataManager.Info

INFO_FILENAME - Static variable in class org.deeplearning4j.rl4j.util.Constants

initMdp(MDP<O, A, AS>, IHistoryProcessor) - Static method in class org.deeplearning4j.rl4j.learning.Learning

initMdp() - Method in class org.deeplearning4j.rl4j.learning.Learning

InitMdp() - Constructor for class org.deeplearning4j.rl4j.learning.Learning.InitMdp

isAtFullCapacity() - Method in class org.deeplearning4j.rl4j.observation.preprocessor.pooling.CircularFifoObservationPool

isAtFullCapacity() - Method in interface org.deeplearning4j.rl4j.observation.preprocessor.pooling.ObservationPool

isDone() - Method in class org.deeplearning4j.rl4j.mdp.toy.HardDeteministicToy

isDone() - Method in class org.deeplearning4j.rl4j.mdp.toy.SimpleToy

isMonitoring() - Method in class org.deeplearning4j.rl4j.learning.HistoryProcessor

isMonitoring() - Method in interface org.deeplearning4j.rl4j.learning.IHistoryProcessor

isRecurrent() - Method in interface org.deeplearning4j.rl4j.network.ac.IActorCritic

isRecurrent() - Method in class org.deeplearning4j.rl4j.network.dqn.DQN

isRecurrent() - Method in interface org.deeplearning4j.rl4j.network.dqn.IDQN

isRecurrent() - Method in interface org.deeplearning4j.rl4j.network.NeuralNet

returns true if this is a recurrent network

isRunning() - Method in interface org.deeplearning4j.rl4j.learning.async.IAsyncGlobal

isSaveData() - Method in interface org.deeplearning4j.rl4j.util.IDataManager

isTrainingComplete() - Method in class org.deeplearning4j.rl4j.learning.async.AsyncGlobal

isTrainingComplete() - Method in class org.deeplearning4j.rl4j.learning.async.AsyncLearning

isTrainingComplete() - Method in interface org.deeplearning4j.rl4j.learning.async.IAsyncGlobal

L

launchThreads() - Method in class org.deeplearning4j.rl4j.learning.async.AsyncLearning

Learning<O extends Encodable,A,AS extends ActionSpace<A>,NN extends NeuralNet> - Class in org.deeplearning4j.rl4j.learning

Learning(ILearning.LConfiguration) - Constructor for class org.deeplearning4j.rl4j.learning.Learning

Learning.InitMdp<O> - Class in org.deeplearning4j.rl4j.learning

load(String) - Static method in class org.deeplearning4j.rl4j.network.ac.ActorCriticCompGraph

load(String, String) - Static method in class org.deeplearning4j.rl4j.network.ac.ActorCriticSeparate

load(String) - Static method in class org.deeplearning4j.rl4j.network.dqn.DQN

load(String) - Static method in class org.deeplearning4j.rl4j.policy.ACPolicy

load(String, Random) - Static method in class org.deeplearning4j.rl4j.policy.ACPolicy

load(String, String) - Static method in class org.deeplearning4j.rl4j.policy.ACPolicy

load(String, String, Random) - Static method in class org.deeplearning4j.rl4j.policy.ACPolicy

load(String) - Static method in class org.deeplearning4j.rl4j.policy.DQNPolicy

load(File, Class<C>) - Static method in class org.deeplearning4j.rl4j.util.DataManager

load(String, Class<C>) - Static method in class org.deeplearning4j.rl4j.util.DataManager

load(InputStream, Class<C>) - Static method in class org.deeplearning4j.rl4j.util.DataManager

M

makeShape(int, int[]) - Static method in class org.deeplearning4j.rl4j.learning.Learning

makeShape(int, int[], int) - Static method in class org.deeplearning4j.rl4j.learning.Learning

maxIndex(double[]) - Static method in class org.deeplearning4j.rl4j.mdp.toy.HardDeteministicToy

mdp - Variable in class org.deeplearning4j.rl4j.learning.async.a3c.discrete.A3CDiscrete

mdp - Variable in class org.deeplearning4j.rl4j.learning.async.a3c.discrete.A3CThreadDiscrete

mdp - Variable in class org.deeplearning4j.rl4j.learning.async.nstep.discrete.AsyncNStepQLearningThreadDiscrete

MiniTrans<A> - Class in org.deeplearning4j.rl4j.learning.async

MiniTrans() - Constructor for class org.deeplearning4j.rl4j.learning.async.MiniTrans

mln - Variable in class org.deeplearning4j.rl4j.network.dqn.DQN

MODEL_DIR - Static variable in class org.deeplearning4j.rl4j.util.Constants

MODEL_SAVE_FREQ - Static variable in class org.deeplearning4j.rl4j.util.Constants

MONITOR_FREQ - Static variable in class org.deeplearning4j.rl4j.util.Constants

monitorFrequency(int) - Method in class org.deeplearning4j.rl4j.util.DataManagerSyncTrainingListener.Builder

A number that represent the number of steps since the last call to HistoryProcessor.startMonitor() before can it be called again.

N

name() - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticLoss

NEURAL_NET_ITERATION_LISTENER - Static variable in class org.deeplearning4j.rl4j.util.Constants

NEURAL_NET_SEED - Static variable in class org.deeplearning4j.rl4j.util.Constants

NeuralNet<NN extends NeuralNet> - Interface in org.deeplearning4j.rl4j.network

NeuralNetFetchable<NN extends NeuralNet> - Interface in org.deeplearning4j.rl4j.learning

newInstance() - Method in class org.deeplearning4j.rl4j.mdp.toy.HardDeteministicToy

newInstance() - Method in class org.deeplearning4j.rl4j.mdp.toy.SimpleToy

newThread(int, int) - Method in class org.deeplearning4j.rl4j.learning.async.a3c.discrete.A3CDiscrete

newThread(int, int) - Method in class org.deeplearning4j.rl4j.learning.async.a3c.discrete.A3CDiscreteConv

newThread(int, int) - Method in class org.deeplearning4j.rl4j.learning.async.AsyncLearning

newThread(int, int) - Method in class org.deeplearning4j.rl4j.learning.async.nstep.discrete.AsyncNStepQLearningDiscrete

newThread(int, int) - Method in class org.deeplearning4j.rl4j.learning.async.nstep.discrete.AsyncNStepQLearningDiscreteConv

nextAction(INDArray) - Method in class org.deeplearning4j.rl4j.policy.ACPolicy

nextAction(INDArray) - Method in class org.deeplearning4j.rl4j.policy.BoltzmannQ

nextAction(INDArray) - Method in class org.deeplearning4j.rl4j.policy.DQNPolicy

nextAction(INDArray) - Method in class org.deeplearning4j.rl4j.policy.EpsGreedy

nextAction(INDArray) - Method in class org.deeplearning4j.rl4j.policy.Policy

O

observablePool(ObservationPool) - Method in class org.deeplearning4j.rl4j.observation.preprocessor.PoolingDataSetPreProcessor.Builder

Default is CircularFifoObservationPool

ObservationPool - Interface in org.deeplearning4j.rl4j.observation.preprocessor.pooling

ObservationPool is used with the PoolingDataSetPreProcessor.

onEpochEnd(SyncTrainingEpochEndEvent) - Method in interface org.deeplearning4j.rl4j.learning.sync.listener.SyncTrainingListener

Called after the end of every epoch.

onEpochEnd(SyncTrainingEpochEndEvent) - Method in class org.deeplearning4j.rl4j.util.DataManagerSyncTrainingListener

onEpochStart(SyncTrainingEvent) - Method in interface org.deeplearning4j.rl4j.learning.sync.listener.SyncTrainingListener

Called before the start of every epoch.

onEpochStart(SyncTrainingEvent) - Method in class org.deeplearning4j.rl4j.util.DataManagerSyncTrainingListener

onTrainingEnd() - Method in interface org.deeplearning4j.rl4j.learning.sync.listener.SyncTrainingListener

Called once when the training has finished.

onTrainingEnd() - Method in class org.deeplearning4j.rl4j.util.DataManagerSyncTrainingListener

onTrainingStart(SyncTrainingEvent) - Method in interface org.deeplearning4j.rl4j.learning.sync.listener.SyncTrainingListener

Called once when the training starts.

onTrainingStart(SyncTrainingEvent) - Method in class org.deeplearning4j.rl4j.util.DataManagerSyncTrainingListener

org.deeplearning4j.rl4j.learning - package org.deeplearning4j.rl4j.learning

org.deeplearning4j.rl4j.learning.async - package org.deeplearning4j.rl4j.learning.async

org.deeplearning4j.rl4j.learning.async.a3c.discrete - package org.deeplearning4j.rl4j.learning.async.a3c.discrete

org.deeplearning4j.rl4j.learning.async.nstep.discrete - package org.deeplearning4j.rl4j.learning.async.nstep.discrete

org.deeplearning4j.rl4j.learning.sync - package org.deeplearning4j.rl4j.learning.sync

org.deeplearning4j.rl4j.learning.sync.listener - package org.deeplearning4j.rl4j.learning.sync.listener

org.deeplearning4j.rl4j.learning.sync.qlearning - package org.deeplearning4j.rl4j.learning.sync.qlearning

org.deeplearning4j.rl4j.learning.sync.qlearning.discrete - package org.deeplearning4j.rl4j.learning.sync.qlearning.discrete

org.deeplearning4j.rl4j.mdp.toy - package org.deeplearning4j.rl4j.mdp.toy

org.deeplearning4j.rl4j.network - package org.deeplearning4j.rl4j.network

org.deeplearning4j.rl4j.network.ac - package org.deeplearning4j.rl4j.network.ac

org.deeplearning4j.rl4j.network.dqn - package org.deeplearning4j.rl4j.network.dqn

org.deeplearning4j.rl4j.observation.preprocessor - package org.deeplearning4j.rl4j.observation.preprocessor

org.deeplearning4j.rl4j.observation.preprocessor.pooling - package org.deeplearning4j.rl4j.observation.preprocessor.pooling

org.deeplearning4j.rl4j.policy - package org.deeplearning4j.rl4j.policy

org.deeplearning4j.rl4j.util - package org.deeplearning4j.rl4j.util

output(INDArray) - Method in class org.deeplearning4j.rl4j.network.dqn.DQN

output(INDArray) - Method in interface org.deeplearning4j.rl4j.network.dqn.IDQN

outputAll(INDArray) - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticCompGraph

outputAll(INDArray) - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticSeparate

outputAll(INDArray) - Method in interface org.deeplearning4j.rl4j.network.ac.IActorCritic

outputAll(INDArray) - Method in class org.deeplearning4j.rl4j.network.dqn.DQN

outputAll(INDArray) - Method in interface org.deeplearning4j.rl4j.network.dqn.IDQN

outputAll(INDArray) - Method in interface org.deeplearning4j.rl4j.network.NeuralNet

P

play(MDP<O, A, AS>) - Method in class org.deeplearning4j.rl4j.policy.Policy

play(MDP<O, A, AS>, IHistoryProcessor.Configuration) - Method in class org.deeplearning4j.rl4j.policy.Policy

play(MDP<O, A, AS>, IHistoryProcessor) - Method in class org.deeplearning4j.rl4j.policy.Policy

Policy<O extends Encodable,A> - Class in org.deeplearning4j.rl4j.policy

Policy() - Constructor for class org.deeplearning4j.rl4j.policy.Policy

policyNet - Variable in class org.deeplearning4j.rl4j.network.ac.ActorCriticSeparate

PoolContentAssembler - Interface in org.deeplearning4j.rl4j.observation.preprocessor.pooling

A PoolContentAssembler is used with the PoolingDataSetPreProcessor.

poolContentAssembler(PoolContentAssembler) - Method in class org.deeplearning4j.rl4j.observation.preprocessor.PoolingDataSetPreProcessor.Builder

Default is ChannelStackPoolContentAssembler

PoolingDataSetPreProcessor - Class in org.deeplearning4j.rl4j.observation.preprocessor

The PoolingDataSetPreProcessor will accumulate features from incoming DataSets and will assemble its content into a DataSet containing a single example.

PoolingDataSetPreProcessor(PoolingDataSetPreProcessor.Builder) - Constructor for class org.deeplearning4j.rl4j.observation.preprocessor.PoolingDataSetPreProcessor

PoolingDataSetPreProcessor.Builder - Class in org.deeplearning4j.rl4j.observation.preprocessor

poolSize(int) - Method in class org.deeplearning4j.rl4j.observation.preprocessor.pooling.CircularFifoObservationPool.Builder

postEpoch() - Method in class org.deeplearning4j.rl4j.learning.async.AsyncThread

postEpoch() - Method in class org.deeplearning4j.rl4j.learning.sync.qlearning.discrete.QLearningDiscrete

postEpoch() - Method in class org.deeplearning4j.rl4j.learning.sync.qlearning.QLearning

postEpoch() - Method in class org.deeplearning4j.rl4j.learning.sync.SyncLearning

preEpoch() - Method in class org.deeplearning4j.rl4j.learning.async.AsyncThread

preEpoch() - Method in class org.deeplearning4j.rl4j.learning.sync.qlearning.discrete.QLearningDiscrete

preEpoch() - Method in class org.deeplearning4j.rl4j.learning.sync.qlearning.QLearning

preEpoch() - Method in class org.deeplearning4j.rl4j.learning.sync.SyncLearning

preProcess(DataSet) - Method in class org.deeplearning4j.rl4j.observation.preprocessor.PoolingDataSetPreProcessor

Note: preProcess will empty the processed dataset if the pool has not filled.

preProcess(DataSet) - Method in class org.deeplearning4j.rl4j.observation.preprocessor.SkippingDataSetPreProcessor

printTest(IDQN) - Static method in class org.deeplearning4j.rl4j.mdp.toy.HardDeteministicToy

printTest(int) - Method in class org.deeplearning4j.rl4j.mdp.toy.SimpleToy

processHistory(INDArray) - Method in class org.deeplearning4j.rl4j.learning.async.AsyncThreadDiscrete

Q

QLConfiguration() - Constructor for class org.deeplearning4j.rl4j.learning.sync.qlearning.QLearning.QLConfiguration

QLConfigurationBuilder() - Constructor for class org.deeplearning4j.rl4j.learning.sync.qlearning.QLearning.QLConfiguration.QLConfigurationBuilder

QLearning<O extends Encodable,A,AS extends ActionSpace<A>> - Class in org.deeplearning4j.rl4j.learning.sync.qlearning

QLearning(QLearning.QLConfiguration) - Constructor for class org.deeplearning4j.rl4j.learning.sync.qlearning.QLearning

QLearning.QLConfiguration - Class in org.deeplearning4j.rl4j.learning.sync.qlearning

QLearning.QLConfiguration.QLConfigurationBuilder - Class in org.deeplearning4j.rl4j.learning.sync.qlearning

QLearning.QLStatEntry - Class in org.deeplearning4j.rl4j.learning.sync.qlearning

QLearning.QLStepReturn<O> - Class in org.deeplearning4j.rl4j.learning.sync.qlearning

QLearningDiscrete<O extends Encodable> - Class in org.deeplearning4j.rl4j.learning.sync.qlearning.discrete

QLearningDiscrete(MDP<O, Integer, DiscreteSpace>, IDQN, QLearning.QLConfiguration, IDataManager, int) - Constructor for class org.deeplearning4j.rl4j.learning.sync.qlearning.discrete.QLearningDiscrete

Deprecated.

Use QLearningDiscrete(MDP, IDQN, QLConfiguration, int) and add the required listeners with addListener() instead.

QLearningDiscrete(MDP<O, Integer, DiscreteSpace>, IDQN, QLearning.QLConfiguration, int) - Constructor for class org.deeplearning4j.rl4j.learning.sync.qlearning.discrete.QLearningDiscrete

QLearningDiscreteConv<O extends Encodable> - Class in org.deeplearning4j.rl4j.learning.sync.qlearning.discrete

QLearningDiscreteConv(MDP<O, Integer, DiscreteSpace>, IDQN, IHistoryProcessor.Configuration, QLearning.QLConfiguration, IDataManager) - Constructor for class org.deeplearning4j.rl4j.learning.sync.qlearning.discrete.QLearningDiscreteConv

QLearningDiscreteConv(MDP<O, Integer, DiscreteSpace>, DQNFactory, IHistoryProcessor.Configuration, QLearning.QLConfiguration, IDataManager) - Constructor for class org.deeplearning4j.rl4j.learning.sync.qlearning.discrete.QLearningDiscreteConv

QLearningDiscreteConv(MDP<O, Integer, DiscreteSpace>, DQNFactoryStdConv.Configuration, IHistoryProcessor.Configuration, QLearning.QLConfiguration, IDataManager) - Constructor for class org.deeplearning4j.rl4j.learning.sync.qlearning.discrete.QLearningDiscreteConv

QLearningDiscreteDense<O extends Encodable> - Class in org.deeplearning4j.rl4j.learning.sync.qlearning.discrete

QLearningDiscreteDense(MDP<O, Integer, DiscreteSpace>, IDQN, QLearning.QLConfiguration, IDataManager) - Constructor for class org.deeplearning4j.rl4j.learning.sync.qlearning.discrete.QLearningDiscreteDense

QLearningDiscreteDense(MDP<O, Integer, DiscreteSpace>, DQNFactory, QLearning.QLConfiguration, IDataManager) - Constructor for class org.deeplearning4j.rl4j.learning.sync.qlearning.discrete.QLearningDiscreteDense

QLearningDiscreteDense(MDP<O, Integer, DiscreteSpace>, DQNFactoryStdDense.Configuration, QLearning.QLConfiguration, IDataManager) - Constructor for class org.deeplearning4j.rl4j.learning.sync.qlearning.discrete.QLearningDiscreteDense

QLStatEntry() - Constructor for class org.deeplearning4j.rl4j.learning.sync.qlearning.QLearning.QLStatEntry

QLStepReturn() - Constructor for class org.deeplearning4j.rl4j.learning.sync.qlearning.QLearning.QLStepReturn

R

record(INDArray) - Method in class org.deeplearning4j.rl4j.learning.HistoryProcessor

record(INDArray) - Method in interface org.deeplearning4j.rl4j.learning.IHistoryProcessor

recurrent - Variable in class org.deeplearning4j.rl4j.network.ac.ActorCriticCompGraph

recurrent - Variable in class org.deeplearning4j.rl4j.network.ac.ActorCriticSeparate

reset() - Method in class org.deeplearning4j.rl4j.mdp.toy.HardDeteministicToy

reset() - Method in class org.deeplearning4j.rl4j.mdp.toy.SimpleToy

reset() - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticCompGraph

reset() - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticSeparate

reset() - Method in interface org.deeplearning4j.rl4j.network.ac.IActorCritic

reset() - Method in class org.deeplearning4j.rl4j.network.dqn.DQN

reset() - Method in interface org.deeplearning4j.rl4j.network.dqn.IDQN

reset() - Method in interface org.deeplearning4j.rl4j.network.NeuralNet

required for recurrent networks during init

reset() - Method in class org.deeplearning4j.rl4j.observation.preprocessor.pooling.CircularFifoObservationPool

reset() - Method in interface org.deeplearning4j.rl4j.observation.preprocessor.pooling.ObservationPool

reset() - Method in class org.deeplearning4j.rl4j.observation.preprocessor.PoolingDataSetPreProcessor

reset() - Method in class org.deeplearning4j.rl4j.observation.preprocessor.ResettableDataSetPreProcessor

reset() - Method in class org.deeplearning4j.rl4j.observation.preprocessor.SkippingDataSetPreProcessor

ResettableDataSetPreProcessor - Class in org.deeplearning4j.rl4j.observation.preprocessor

A base class for all DataSetPreProcessor that must be reset between each MDP sessions (games).

ResettableDataSetPreProcessor() - Constructor for class org.deeplearning4j.rl4j.observation.preprocessor.ResettableDataSetPreProcessor

run() - Method in class org.deeplearning4j.rl4j.learning.async.AsyncGlobal

run() - Method in class org.deeplearning4j.rl4j.learning.async.AsyncThread

S

save(OutputStream) - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticCompGraph

save(String) - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticCompGraph

save(OutputStream, OutputStream) - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticCompGraph

save(String, String) - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticCompGraph

save(OutputStream) - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticSeparate

save(String) - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticSeparate

save(OutputStream, OutputStream) - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticSeparate

save(String, String) - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticSeparate

save(OutputStream, OutputStream) - Method in interface org.deeplearning4j.rl4j.network.ac.IActorCritic

save(String, String) - Method in interface org.deeplearning4j.rl4j.network.ac.IActorCritic

save(OutputStream) - Method in class org.deeplearning4j.rl4j.network.dqn.DQN

save(String) - Method in class org.deeplearning4j.rl4j.network.dqn.DQN

save(OutputStream) - Method in interface org.deeplearning4j.rl4j.network.NeuralNet

save the neural net into an OutputStream

save(String) - Method in interface org.deeplearning4j.rl4j.network.NeuralNet

save the neural net into a filename

save(String) - Method in class org.deeplearning4j.rl4j.policy.ACPolicy

save(String, String) - Method in class org.deeplearning4j.rl4j.policy.ACPolicy

save(String) - Method in class org.deeplearning4j.rl4j.policy.DQNPolicy

save(String, Learning) - Static method in class org.deeplearning4j.rl4j.util.DataManager

save(OutputStream, Learning) - Static method in class org.deeplearning4j.rl4j.util.DataManager

save(Learning) - Method in class org.deeplearning4j.rl4j.util.DataManager

save(Learning) - Method in interface org.deeplearning4j.rl4j.util.IDataManager

saveFrequency(int) - Method in class org.deeplearning4j.rl4j.util.DataManagerSyncTrainingListener.Builder

A number that represent the number of steps since the last call to DataManager.save() before can it be called again.

setHistoryProcessor(IHistoryProcessor.Configuration) - Method in class org.deeplearning4j.rl4j.learning.async.AsyncThread

setHistoryProcessor(IHistoryProcessor) - Method in class org.deeplearning4j.rl4j.learning.async.AsyncThread

setHistoryProcessor(IHistoryProcessor.Configuration) - Method in class org.deeplearning4j.rl4j.learning.Learning

setHistoryProcessor(IHistoryProcessor) - Method in class org.deeplearning4j.rl4j.learning.Learning

setRunning(boolean) - Method in interface org.deeplearning4j.rl4j.learning.async.IAsyncGlobal

setTarget(ArrayList<Transition<Integer>>) - Method in class org.deeplearning4j.rl4j.learning.sync.qlearning.discrete.QLearningDiscrete

setTargetDQN(IDQN) - Method in class org.deeplearning4j.rl4j.learning.sync.qlearning.QLearning

show(Mat) - Method in class org.deeplearning4j.rl4j.learning.HistoryProcessor

SimpleToy - Class in org.deeplearning4j.rl4j.mdp.toy

SimpleToy(int) - Constructor for class org.deeplearning4j.rl4j.mdp.toy.SimpleToy

SimpleToyState - Class in org.deeplearning4j.rl4j.mdp.toy

SimpleToyState() - Constructor for class org.deeplearning4j.rl4j.mdp.toy.SimpleToyState

SkippingDataSetPreProcessor - Class in org.deeplearning4j.rl4j.observation.preprocessor

The SkippingDataSetPreProcessor will either do nothing to the input (when not skipped) or will empty the input DataSet when skipping.

SkippingDataSetPreProcessor(int) - Constructor for class org.deeplearning4j.rl4j.observation.preprocessor.SkippingDataSetPreProcessor

start() - Method in interface org.deeplearning4j.rl4j.learning.async.IAsyncGlobal

startGlobalThread() - Method in class org.deeplearning4j.rl4j.learning.async.AsyncLearning

startMonitor(String, int[]) - Method in class org.deeplearning4j.rl4j.learning.HistoryProcessor

startMonitor(String, int[]) - Method in interface org.deeplearning4j.rl4j.learning.IHistoryProcessor

STATISTIC_FILENAME - Static variable in class org.deeplearning4j.rl4j.util.Constants

step(Integer) - Method in class org.deeplearning4j.rl4j.mdp.toy.HardDeteministicToy

step(Integer) - Method in class org.deeplearning4j.rl4j.mdp.toy.SimpleToy

StepCountable - Interface in org.deeplearning4j.rl4j.learning

stopMonitor() - Method in class org.deeplearning4j.rl4j.learning.HistoryProcessor

stopMonitor() - Method in interface org.deeplearning4j.rl4j.learning.IHistoryProcessor

store(Transition<A>) - Method in class org.deeplearning4j.rl4j.learning.sync.ExpReplay

store(Transition<A>) - Method in interface org.deeplearning4j.rl4j.learning.sync.IExpReplay

SubEpochReturn() - Constructor for class org.deeplearning4j.rl4j.learning.async.AsyncThread.SubEpochReturn

SyncLearning<O extends Encodable,A,AS extends ActionSpace<A>,NN extends NeuralNet> - Class in org.deeplearning4j.rl4j.learning.sync

Mother class and useful factorisations for all training methods that are not asynchronous.

SyncLearning(ILearning.LConfiguration) - Constructor for class org.deeplearning4j.rl4j.learning.sync.SyncLearning

SyncTrainingEpochEndEvent - Class in org.deeplearning4j.rl4j.learning.sync.listener

A subclass of SyncTrainingEvent that is passed to SyncTrainingListener.onEpochEnd()

SyncTrainingEpochEndEvent(Learning, IDataManager.StatEntry) - Constructor for class org.deeplearning4j.rl4j.learning.sync.listener.SyncTrainingEpochEndEvent

SyncTrainingEvent - Class in org.deeplearning4j.rl4j.learning.sync.listener

SyncTrainingEvent are passed as parameters to the events of SyncTrainingListener

SyncTrainingEvent(Learning) - Constructor for class org.deeplearning4j.rl4j.learning.sync.listener.SyncTrainingEvent

SyncTrainingListener - Interface in org.deeplearning4j.rl4j.learning.sync.listener

A listener interface to use with a descendant of SyncLearning

SyncTrainingListener.ListenerResponse - Enum in org.deeplearning4j.rl4j.learning.sync.listener

T

targetDqnOutput(INDArray) - Method in class org.deeplearning4j.rl4j.learning.sync.qlearning.QLearning

threadNumber - Variable in class org.deeplearning4j.rl4j.learning.async.a3c.discrete.A3CThreadDiscrete

threadNumber - Variable in class org.deeplearning4j.rl4j.learning.async.nstep.discrete.AsyncNStepQLearningThreadDiscrete

toArray() - Method in class org.deeplearning4j.rl4j.mdp.toy.HardToyState

toArray() - Method in class org.deeplearning4j.rl4j.mdp.toy.SimpleToyState

toString() - Method in class org.deeplearning4j.rl4j.network.ac.ActorCriticLoss

train() - Method in class org.deeplearning4j.rl4j.learning.async.AsyncLearning

train() - Method in interface org.deeplearning4j.rl4j.learning.ILearning

train() - Method in class org.deeplearning4j.rl4j.learning.sync.SyncLearning

This method will train the model

trainEpoch() - Method in class org.deeplearning4j.rl4j.learning.sync.qlearning.QLearning

trainEpoch() - Method in class org.deeplearning4j.rl4j.learning.sync.SyncLearning

trainStep(O) - Method in class org.deeplearning4j.rl4j.learning.sync.qlearning.discrete.QLearningDiscrete

Single step of training

trainStep(O) - Method in class org.deeplearning4j.rl4j.learning.sync.qlearning.QLearning

trainSubEpoch(O, int) - Method in class org.deeplearning4j.rl4j.learning.async.AsyncThread

trainSubEpoch(O, int) - Method in class org.deeplearning4j.rl4j.learning.async.AsyncThreadDiscrete

"Subepoch" correspond to the t_max-step iterations that stack rewards with t_max MiniTrans

Transition<A> - Class in org.deeplearning4j.rl4j.learning.sync

Transition() - Constructor for class org.deeplearning4j.rl4j.learning.sync.Transition

U

updateTargetNetwork() - Method in class org.deeplearning4j.rl4j.learning.sync.qlearning.QLearning

V

valueNet - Variable in class org.deeplearning4j.rl4j.network.ac.ActorCriticSeparate

valueOf(String) - Static method in enum org.deeplearning4j.rl4j.learning.sync.listener.SyncTrainingListener.ListenerResponse

Returns the enum constant of this type with the specified name.

values() - Static method in enum org.deeplearning4j.rl4j.learning.sync.listener.SyncTrainingListener.ListenerResponse

Returns an array containing the constants of this enum type, in the order they are declared.

VIDEO_DIR - Static variable in class org.deeplearning4j.rl4j.util.Constants

W

waitKP() - Method in class org.deeplearning4j.rl4j.learning.HistoryProcessor

writeInfo(ILearning) - Method in class org.deeplearning4j.rl4j.util.DataManager

writeInfo(ILearning) - Method in interface org.deeplearning4j.rl4j.util.IDataManager

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