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.