MAgent
ma-gym
MAgent | ma-gym | |
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2 | 2 | |
1,667 | 522 | |
1.3% | - | |
0.0 | 4.4 | |
over 1 year ago | 12 days ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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MAgent
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[N] MAgent2 - a reinforcement learning environment engine that can allows for efficient multi-agent games with hundreds or thousands of agents- is now mature within the Farama Foundation
MAgent2 is the maintained fork of the environments in https://github.com/geek-ai/MAgent, which previously were housed in PettingZoo itself but as of a few months ago was broken off into it's own project. You can check it out here: https://magent2.farama.org/ / https://github.com/Farama-Foundation/magent2
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MAgent2 - a reinforcement learning environment engine that can allows for efficient multi-agent games with hundreds or thousands of agents- is now mature within the Farama Foundation
It's the maintained fork of the environments in https://github.com/geek-ai/MAgent, which previously were housed in PettingZoo itself but as of a few months ago were broken off into their own project
ma-gym
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Tensorflow and OpenAI Gym for Multi-Agent Reinforcement Learning?
Of course I conducted research (or rather... searched on google :)) before making this post. I found a simple third party gym environment that implements multi-agent rl called 'ma-gym' (https://github.com/koulanurag/ma-gym) but I'm not quite sure how I would train two Agents and let them play inside one environment.
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How do you train Agent for something like Chess or Game of the Generals?
There are projects working on a multi agent version of gym. Maybe you find some inspiration there.
What are some alternatives?
MAgent2 - An engine for high performance multi-agent environments with very large numbers of agents, along with a set of reference environments
mcts-general - General Python implementation of Monte Carlo Tree Search for the use with Open AI Gym environments.
Minigrid - Simple and easily configurable grid world environments for reinforcement learning
crafter - Benchmarking the Spectrum of Agent Capabilities
Super-mario-bros-PPO-pytorch - Proximal Policy Optimization (PPO) algorithm for Super Mario Bros
GoBigger - [ICLR 2023] Come & try Decision-Intelligence version of "Agar"! Gobigger could also help you with multi-agent decision intelligence study.
rlcard - Reinforcement Learning / AI Bots in Card (Poker) Games - Blackjack, Leduc, Texas, DouDizhu, Mahjong, UNO.