Sparse Adversarial Attack in Multi-agent Reinforcement Learning

no code implementations • 19 May 2022 • Yizheng Hu, Zhihua Zhang

Cooperative multi-agent reinforcement learning (cMARL) has many real applications, but the policy trained by existing cMARL algorithms is not robust enough when deployed.

Adversarial Attack Multi-agent Reinforcement Learning +2

Robust Multi-Agent Reinforcement Learning Driven by Correlated Equilibrium

no code implementations • 1 Jan 2021 • Yizheng Hu, Kun Shao, Dong Li, Jianye Hao, Wulong Liu, Yaodong Yang, Jun Wang, Zhanxing Zhu

Therefore, to achieve robust CMARL, we introduce novel strategies to encourage agents to learn correlated equilibrium while maximally preserving the convenience of the decentralized execution.

Adversarial Robustness reinforcement-learning +2