MALib: A parallel framework for population-based multi-agent reinforcement learning

• malib

  2 464 3.4 Python

  A parallel framework for population-based multi-agent reinforcement learning.

  

Hey, guys, I'm Ming Zhou from Shanghai Jiao Tong University, a Ph.D. student from Shanghai Jiao Tong University. We recently published a parallel framework for multi-agent learning at GitHub, that is, MALib: A parallel framework for population-based multi-agent reinforcement learning. MALib is a parallel framework of population-based learning nested with (multi-agent) reinforcement learning (RL) methods, such as Policy Space Response Oracle and Neural Fictitious Self-Play. MALib provides higher-level abstractions of MARL training paradigms, which enables efficient code reuse and flexible deployments on different distributed computing paradigms. We hope that this work can promote the research of multi-agent reinforcement learning, especially in large-scale scenarios. Currently, we're working hard to perfect the functionalities and integrate the existing features. People can also read our paper here 👉 https://arxiv.org/abs/2106.07551

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