TF-Agents

E97077

open-source project reinforcement learning framework software library

TF-Agents is an open-source library built on TensorFlow that provides modular components and tools for developing, training, and evaluating reinforcement learning algorithms.

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All labels observed (2)

Label	Occurrences
TF-Agents canonical	1
TensorFlow Agents	1

Statements (49)

Predicate	Object
instanceOf	open-source project ⓘ reinforcement learning framework ⓘ software library ⓘ
basedOn	TensorFlow ⓘ
designedFor	production reinforcement learning systems ⓘ research in reinforcement learning ⓘ
developedBy	Google ⓘ Google Brain ⓘ surface form: Google Brain team
hasComponent	agents ⓘ bandits library ⓘ drivers ⓘ environments ⓘ metrics ⓘ networks ⓘ policies ⓘ replay buffers ⓘ
hasFeature	data collection drivers ⓘ distributional RL support ⓘ experience replay ⓘ multi-armed bandits support ⓘ
hostedOn	GitHub ⓘ
isOpenSource	true ⓘ
license	Apache License 2.0 ⓘ
programmingLanguage	Python ⓘ
provides	documentation ⓘ example notebooks ⓘ modular components ⓘ tools for developing reinforcement learning algorithms ⓘ tools for evaluating reinforcement learning algorithms ⓘ tools for training reinforcement learning algorithms ⓘ
supports	TensorFlow ⓘ surface form: TensorFlow 2 continuous action spaces ⓘ discrete action spaces ⓘ eager execution ⓘ off-policy algorithms ⓘ on-policy algorithms ⓘ reinforcement learning ⓘ tf.function graphs ⓘ
supportsAlgorithmFamily	DDPG ⓘ Atari deep Q-network ⓘ surface form: DQN PPO ⓘ REINFORCE ⓘ SAC ⓘ TD3 ⓘ actor-critic methods ⓘ policy gradient methods ⓘ
supportsEnvironment	Atari environments ⓘ MuJoCo environments ⓘ OpenAI Gym ⓘ

Referenced by (2)

Full triples — surface form annotated when it differs from this entity's canonical label.

TensorFlow → hasComponent → TF-Agents ⓘ

PPO → implementedIn → TF-Agents ⓘ

this entity surface form: TensorFlow Agents