Farama-Foundation/MAgent2
An engine for high performance multi-agent environments with very large numbers of agents, along with a set of reference environments
What it solves
MAgent2 provides a platform for simulating large numbers of agents in a gridworld environment where they can interact in competitive scenarios, such as battles, to study artificial collective intelligence.
How it works
It is a library that creates pixel-based gridworld environments. It implements reference environments using the PettingZoo API, allowing researchers to benchmark and train agents in multi-agent reinforcement learning settings.
Who it’s for
Researchers and developers working on multi-agent reinforcement learning (MARL) and collective intelligence.
Highlights
- Pixel-based gridworld environments
- Support for large numbers of agents
- Integrated with the PettingZoo API
- Maintained fork of the original MAgent codebase
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