Toward Rapid and Optimal Strategy for Swarm Conflict: A Computational Game Approach

The decision and control problem for swarm operations is crucial for autonomous military conflict management. In this article, the underlying decision and control problem is treated as a noncooperative game problem, in which the underlying target assignment problem is generalized to be a graph-theoretic problem. We introduce an algorithm to seek the desired Nash equilibrium with the help of the parallel maximum weight matching algorithm. Then, we prove that the proposed solution is epsilon-Nash with guaranteed computational efficiency, and is well suited for the swarm conflict. Simulation results verified the effectiveness of the proposed solutions.