Team search tactics through multi-agent HyperNEAT

Abstract

User defined tactics for teams of unmanned systems can be brittle and difficult to define. The state and action space grows with each new system added to the team which increases the difficultly in designing robust behaviors. In this paper we present a method for using Multiagent HyperNEAT to develop tactics for a team of simulated unmanned systems that is robust to novel situations, and scales with the number of team members. We focus on the tactics of a search area coverage task, where the need for team work, and robust asset management are critical to success.