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ma-gym

Active·★ 631·Updated 2024-07-07
★ Trending

A collection of multi agent environments based on OpenAI gym.

ma-gym provides a collection of multi-agent environments built upon the OpenAI Gym interface, facilitating research and development in multi-agent reinforcement learning. It includes various game-like and task-based environments, as well as wrappers to convert single-agent Gym environments into multi-agent forms for debugging.

#Reinforcement Learning#Multi-Agent Systems#OpenAI Gym#Python#Simulation#Coding
$ Install
$ pip install ma-gym
↗ Visit site★ GitHub
01

Features

01Collection of diverse multi-agent environments (e.g., Checkers, Combat, PredatorPrey, TrafficJunction)
02Built on familiar OpenAI Gym API for easy integration
03Includes a 'multi-agent wrapper' for single-agent OpenAI environments for debugging
04Compatible with multi-agent reinforcement learning frameworks like minimal-marl
05Well-documented with Wiki pages for usage and environment details
02

Compatibility

OpenAI Gym
Native
Verified via docs
Python
Supported
Verified via docs
Google Colab
Supported
Verified via docs
minimal-marl
Supported
Verified via docs
03

Quick start

1
$ pip install ma-gym
04

Use cases

↳Research and experimentation in multi-agent reinforcement learning algorithms
↳Development and testing of multi-agent policies and strategies
↳Educational tool for understanding multi-agent interaction and control
05

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Related searches

ma-gym AlternativesBest Multi-Agent Tools 2026Open Source Multi-Agentma-gym Tutorialma-gym Vs CompetitorsReinforcement LearningMulti-Agent SystemsOpenAI Gym

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On this page
01Features02Compatibility03Quick start04Use cases05Alternatives
Stats
GitHub Stars★ 631
Last commit1y ago
StatusActive
License—
CategoryMulti-Agent
Trend (30d)
+25.2↑ 3.9%
Links
Documentation↗Discussion↗Issues↗Releases↗

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