PettingZoo

E95191

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

All labels observed (1)

Label Occurrences
PettingZoo canonical 3

How this entity was disambiguated

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 ⓘ

How these facts were elicited

Referenced by (3)

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

OpenAI Gym → influenced → PettingZoo ⓘ
Gymnasium → relatedTo → PettingZoo ⓘ