Evolving Optimal Parameters for Swarm Control

Using many inexpensive rovers in place of single costly ones is an idea that has been gaining attention in the last decade. How to effectively control those rovers is an open question, but swarming is an attractive option to present. While much research in the field investigates intelligent swarming, recent research has shown that the unintelligent swarm is an effective control mechanism for thoroughly covering a space and maintaining swarm-like behavior in the face of widespread failures. This paper takes that research one step further, exploring the application of a genetic algorithm to evolve optimal parameters for an exploratory swarm.