Donghui Li

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization

2025 · Proceedings of the AAAI Conference on Artificial Intelligence

Offline Multi-Agent Reinforcement Learning (MARL) is an emerging field that aims to learn optimal multi-agent policies from pre-collected datasets. Compared to single-agent case, multi-agent setting involves a large joint state-action space and coupled behaviors of …