Demo: A multi-agent communication reinforcement learning Cooperative Detection System
Hongye Gao, Yichen Shi, Weixiong Rao, Qiongmin Ma · 2023
Communication is an effective mechanism to coordinate the behavior of mobile multi-agents. We propose a general multi-agent communication framework. With help of graph neural networks and reinforcement learning, this framework can provide a cooperative detection method with more powerful capabilities. In this paper, we demonstrate the configurable co-detection simulation system. Moreover, the evaluation of the multi-agent communication framework validates that the agents can effectively cooperate with each other through decentralized communication, and effectively reduce computation overhead meanwhile with high scalability.