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JaxMARL

JaxMARL - A multi-agent reinforcement learning library

CommonProductProgrammingReinforcement LearningMulti-Agent

JaxMARL is a multi-agent reinforcement learning library that combines ease of use with GPU accelerated performance. It supports common multi-agent reinforcement learning environments and popular benchmark algorithms. The goal is to provide a comprehensive library for evaluating multi-agent reinforcement learning methods and comparing them with related benchmarks. It also introduces SMAX, a simplified version of the popular StarCraft Multi-Agent Challenge environment, which does not require running the StarCraft II game engine.

JaxMARL

Supports multi-agent reinforcement learning environments
Supports multiple benchmark algorithms
User-friendly
Supports GPU acceleration

Used for research and development of multi-agent reinforcement learning.

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