Near-Optimal Multi-Agent Learning for Safe Coverage Control

Neural Information Processing Systems 

In multi-agent coverage control problems, agents navigate their environment to reach locations that maximize the coverage of some density. In practice, the density is rarely known a priori, further complicating the original NP-hard problem.