Multi-agent Collaborative Learning with Relational Graph Reasoning in Adversarial Environments
Shiguang Wu,Tenghai Qiu,Zhiqiang Pu,Jianqiang Yi,Shiguang Wu,Tenghai Qiu,Zhiqiang Pu,Jianqiang Yi
This paper proposes a collaborative policy framework via relational graph reasoning for multi-agent systems to accomplish adversarial tasks. A relational graph reasoning module consisting of an agent graph reasoning module and an opponent graph module, is designed to enable each agent to learn mixture state representation to enhance the effectiveness of the policy. In particular, for each agent, t...
