ethanluoyc/magi
Reinforcement learning library in JAX.
This library helps machine learning researchers and practitioners implement and experiment with reinforcement learning (RL) algorithms. It takes your defined RL environments and agent architectures as input, and outputs trained models capable of learning optimal strategies. Researchers, AI developers, and academics focusing on advanced machine learning would use this to build and test new RL systems.
101 stars. No commits in the last 6 months.
Use this if you are a machine learning researcher or developer working with reinforcement learning and need a flexible, JAX-based framework that offers agents not found in DeepMind's Acme library, along with experiment logging integrations.
Not ideal if you are looking for a stable, production-ready library, as it is in alpha development and expects breaking changes.
Stars
101
Forks
3
Language
Python
License
Apache-2.0
Category
Last pushed
Oct 22, 2023
Commits (30d)
0
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