PettingZoo

E95191

Python library multi-agent reinforcement learning framework

PettingZoo is a Python library that provides a standardized interface and tools for developing, running, and benchmarking multi-agent reinforcement learning environments.

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All labels observed (1)

Label	Occurrences
PettingZoo canonical	3

Statements (47)

Predicate	Object
instanceOf	Python library ⓘ multi-agent reinforcement learning framework ⓘ
aimsTo	improve reproducibility in multi-agent reinforcement learning research ⓘ simplify comparison of multi-agent RL algorithms ⓘ
compatibleWith	RLlib ⓘ Stable Baselines ⓘ surface form: Stable-Baselines3 (via wrappers) Tianshou ⓘ
documentationURL	https://pettingzoo.farama.org ⓘ
domain	artificial intelligence ⓘ
focusesOn	standardization of multi-agent RL interfaces ⓘ
hasAPIStyle	AEC API ⓘ classic API ⓘ parallel API ⓘ
hasEnvironmentType	Arcade Learning Environment ⓘ surface form: Atari multi-agent environments MPE (Multi-Agent Particle Environments) ⓘ board games ⓘ butterfly environments ⓘ classic control ⓘ
hasFeature	environment versioning ⓘ seeding for reproducible experiments ⓘ support for vectorized environments ⓘ wrappers for environment preprocessing ⓘ
hostedOn	GitHub ⓘ
inspiredBy	OpenAI Gym ⓘ
license	MIT License ⓘ
maintainer	Farama Foundation ⓘ
partOf	Farama Foundation ecosystem ⓘ
programmingLanguage	Python ⓘ
provides	standardized interface for multi-agent environments ⓘ tools for benchmarking multi-agent environments ⓘ tools for developing multi-agent environments ⓘ tools for running multi-agent environments ⓘ
relatedTo	Gymnasium ⓘ SuperSuit ⓘ
subdomain	multi-agent systems ⓘ reinforcement learning ⓘ
supports	multi-agent reinforcement learning environments ⓘ
supportsActionSpace	continuous action spaces ⓘ discrete action spaces ⓘ
supportsAgents	competitive agents ⓘ cooperative agents ⓘ mixed cooperative-competitive agents ⓘ
supportsObservationSpace	continuous observation spaces ⓘ discrete observation spaces ⓘ
usedFor	benchmarking multi-agent RL algorithms ⓘ education in reinforcement learning ⓘ research in multi-agent reinforcement learning ⓘ

Referenced by (3)

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

OpenAI Gym → influenced → PettingZoo ⓘ

RLlib → supportsEnvironmentInterface → PettingZoo ⓘ

Gymnasium → relatedTo → PettingZoo ⓘ