Efficient Domain Coverage for Vehicles with Second-Order Dynamics via Multi-Agent Reinforcement Learning
Xinyu Zhao,Razvan C. Fetecau,Mo Chen,Xinyu Zhao,Razvan C. Fetecau,Mo Chen
Collaborative autonomous multi-agent systems covering a specified area have many potential applications. Traditional approaches for such problems involve designing model-based control policies; however, state-of-the-art classical control policy still exhibits a large degree of sub-optimality. We present a combined reinforcement learning (RL) and control approach for the multi-agent coverage proble...
