MARL in real scenarios is still challenging due to the same safety and efficiency concerns in single-agent setting, then it is worth conducting investigation for offline RL in multi-agent setting.

Work done during an internship at Zoox 37th Conference on Neural Information Processing Systems (NeurIPS 2023).

We present a novel multi-agent RL approach, Selective Multi-Agent Prioritized Experience Relay, in which agents share with other agents a limited number of transitions they observe during training.

Simulation of autonomous vehicle systems requires that simulated traffic participants exhibit diverse and realistic behaviors.

In IMP, a multi-component engineering system is subject to a risk of failure due to its components' damage condition.

This paper explores the potential of building scalable techniques to facilitate autonomous cooperation among communicative agents, and provides insight into their "cognitive" processes. To address the challenges of achieving autonomous cooperation, we propose a novel communicative agent framework named roleplaying .