Beta Version 2.0.0
Added
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Added SoftActorCritic, DeepDeterministicPolicyGradient and TwinDelayedDeepDeterministicPolicyGradient under “Models” section.
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DeepQLearning, DeepStateActionRewardStateAction, DeepExpectedStateActionRewardStateAction, ProximalPolicyOptimization models and its variants now have “lambda” argument for TD-Lambda and GAE-Lambda functionality. This includes AdvantageActorCritic model.
Changes
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All internal components now uses TensorL2D instead of MatrixL for full compatibility with DataPredict Neural. TensorL2D can be replaced with TensorL.
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All constructors now requires a parameter dictionary instead of arguments.
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The diagonalGaussianUpdate() function now requires actionNoiseVector.
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Moved RandomNetworkDistillation, GenerativeAdversarialImitationLearning and WassersteinGenerativeAdversarialImitationLearning to “ReinforcementLearningStrategies” section.
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Renamed DistributedGradients to DistributedGradientsCoordinator and moved to “DistributedTrainingStrategies” section.
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Renamed DistributedModelParameters to DistributedModelParametersCoordinator and moved to “DistributedTrainingStrategies” section.
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All reinforcement learning models now require “terminalStateValue” for categoricalUpdate(), diagonalGaussianUpdate() and episodeUpdate() functions.
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Reimplemented ActorCritic, VanillaPolicyGradient and REINFORCE models.
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Made major changes with ModelChecker, ModelDatasetCreator and OnlineTraining under the “Other” section.
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CategoricalPolicyQuickSetup and DiagonalGaussianPolicyQuickSetup no longer have setClassesList() and getClassesList() functions.
Fixes
- Fixed CategoricalPolicyQuickSetup and DiagonalGaussianPolicyQuickSetup, where the next action is used in the categoricalUpdate() and diagonalGaussianUpdate() instead of previous action.
Removed
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Removed AsynchronousAdvantageActorCritic from “Models” to reduce maintenance effort. You can use AdvantageActorCritic with DistributedGradientsCoordinator or DistributedModelParametersCoordinator to achieve similar functionalities.
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Removed “AqwamCustomModels” section and its models.