MARPO: A Reflective Policy Optimization for Multi Agent Reinforcement Learning

This article introduces MARPO, a new approach to multi-agent reinforcement learning. The title suggests a focus on reflective policy optimization, implying the algorithm learns by analyzing and improving its own decision-making process. The source being ArXiv indicates this is a research paper, likely detailing the methodology, experiments, and results of MARPO.