May 10, 2023 · We propose Robust Multi-Agent Coordination via Evolutionary Generation of Auxiliary Adversarial Attackers (ROMANCE), which enables the trained policy to ...

We then propose ROMANCE, an efficient approach to learn robust multi-agent coordination via evolutionary generation of auxiliary adversarial attackers.

Policy learned without ROMANCE ignores the emergent situation and still tries to assault when the attacked marauder is drawn away. • Policy learned with ROMANCE ...

Feb 7, 2023 · Cooperative multi-agent reinforcement learning (CMARL) has shown to be promising for many real-world applications.

Cooperative Multi-agent Reinforcement Learning (CMARL) has shown to be promising for many real-world applications. Previous works mainly focus on improving ...

Robust Multi-agent Coordination via Evolutionary Generation of Auxiliary Adversarial Attackers. This work is accepted as Oral at the Association for the ...

Then, we propose Robust Multi-Agent Coordination via Evolutionary Generation of Auxiliary Adversarial Attackers (ROMANCE), which enables the trained policy to ...

ROMANCE: Robust Multi-agent Coordination via Evolutionary Generation of Auxiliary Adversarial Attackers. 48分钟. 2696播放. Multi-agent Dynamic Algorithm ...

Cooperative multi-agent reinforcement learning (CMARL) has shown to be promising for many real-world applications.

Many multi-agent scenarios require message sharing among agents to promote coordination, hastening the robustness of multi-agent communication when policies are ...