Targets-Attackers-Defenders Game via Pairwise Outcomes

Decision algorithms are one of the key areas of focus in cluster confrontation research. In this paper, a Targets-Attackers-Defenders (TADs) game that includes an attacking team with NA Attackers, a target team with NT targets and a defending team with ND Defenders is considered. In this game, the players within each team cooperate with each other, and both cooperation and confrontation between the teams ensue. The defending team cooperates with the target team against the attacking team. The attacking team aims to capture NT Targets. The defending team protects NT Targets by intercepting Attackers or rendezvousing with Targets. We present a maximum matching algorithm considering both confrontation and cooperation by using relative distance and velocity parameters, and transform the TADs problem into a real-time target-assignment problem with strong confrontation. Finally, we propose an improved basic variable neighborhood search algorithm to solve the target-assignment problem and give the optimal dynamical strategy for each player.