Metadata-Version: 2.1
Name: PettingZoo
Version: 0.1.3
Summary: Gym for multi-agent reinforcement learning
Home-page: https://github.com/PettingZoo-Team/PettingZoo
Author: PettingZoo Team
Author-email: justinkterry@gmail.com
License: UNKNOWN
Description: # PettingZoo
        PettingZoo is Python library for conducting research in multi-agent reinforcement learning. It's akin to a multi-agent version of OpenAI's Gym library.
        
        We model environments as *Agent Environment Cycle* (AEC) games, in order to be able to support all types of multi-agent RL environments under one API.
        
        ## Environment Types and Installation
        
        PettingZoo includes the following sets of games:
        
        * atari: Multi-player Atari 2600 games (both cooperative and competitive)
        * classic: Classical, nongraphical, competitive games (i.e. chess, Texas hold 'em, and go)
        * gamma: Cooperative graphical games developed by us. Policies for these must learn very coordinated behaviors.
        * magent: Environments with massive numbers of particle agents, originally from https://github.com/geek-ai/MAgent
        * mpe: A set of simple nongraphical communication tasks, originally from https://github.com/openai/multiagent-particle-envs
        * sisl: 3 cooperative environments, originally from https://github.com/sisl/MADRL
        
        To install, use `pip install pettingzoo` 
        
        We support Python 3.5, 3.6, 3.7 and 3.8
        
        
        
Keywords: Reinforcement Learning,game,RL,AI,gym
Platform: UNKNOWN
Requires-Python: >=3.5
Description-Content-Type: text/markdown
