Distributed Solving of Weapon Target Assignment Problem using Learning Automata

This article presents a method to solve the weapon target assignment problem, which is one of the problems of distributed constraint optimization. The previous methods do not guarantee the convergence problem properly and when faced with scale increase, they do not work correctly and effectively. Also, some of these methods solve the weapon target assignment problem in a centralized manner. While the method presented in this article solves the problem in a decentralized and distributed manner with better "accuracy" and "speed".The present article solves the weapon target assignment problem by using learning automata, which is a relatively simple method and requires little information, and the results of implementations show that when the scale of the problem becomes larger, the proposed method it solves the problem with a better speed than other methods, so that the objective function is minimized. Also, this method can well address the shortcomings of previous methods without the need for other exploratory methods in real-time multi-agent environments.