Shi, Zhaoyang

Community-based Multi-Agent Reinforcement Learning with Transfer and Active Exploration

2025 · arXiv (Cornell University)

We propose a new framework for multi-agent reinforcement learning (MARL), where the agents cooperate in a time-evolving network with latent community structures and mixed memberships. Unlike traditional neighbor-based or fixed interaction graphs, our community-based framework …