Ningze Zhong

MangoBench: A Benchmark for Multi-Agent Goal-Conditioned Offline Reinforcement Learning

Offline Multi-Agent Reinforcement Learning (MARL) is critical for coordinating multiple agents in costly and unsafe environments, yet existing methods struggle with high sensitivity to reward functions and weak generalization to new goals, limiting its practical impact. Inspired by single-agent Offl