Coevolutionary Algorithm for Evolving Competitive Strategies in the Weapon Target Assignment Problem

This paper considers a non-cooperative real-time strategy game between two teams; each has multiple homogeneous players with identical capabilities. In particular, the first team consists of multiple land vehicles under attack by a team of drones, and the vehicles are equipped with weapons to counterattack the drones. However, with the increase in the number of drones, it may become difficult for human operators to coordinate actions across vehicles in a timely manner. Therefore, we explore a coevolutionary approach to simultaneously evolve competitive weapon target assignment strategies for the land vehicles and drone threats to address this problem. Different scenarios involving a different number of land vehicles and drone threats have been considered to evaluate the performance of the proposed approach. Results showed some advantages of applying such a coevolutionary approach.