Title :
A predator-prey particle swarm optimization approach to multiple UCAV air combat modeled by dynamic game theory
Author :
Haibin Duan ; Pei Li ; Yaxiang Yu
Author_Institution :
Sci. & Technol. on Aircraft Control Lab., Beihang Univ. (BUAA), Beijing, China
Abstract :
Dynamic game theory has received considerable attention as a promising technique for formulating control actions for agents in an extended complex enterprise that involves an adversary. At each decision making step, each side seeks the best scheme with the purpose of maximizing its own objective function. In this paper, a game theoretic approach based on predatorprey particle swarm optimization (PP-PSO) is presented, and the dynamic task assignment problem for multiple unmanned combat aerial vehicles (UCAVs) in military operation is decomposed and modeled as a two-player game at each decision stage. The optimal assignment scheme of each stage is regarded as a mixed Nash equilibrium, which can be solved by using the PP-PSO. The effectiveness of our proposed methodology is verified by a typical example of an air military operation that involves two opposing forces: the attacking force Red and the defense force Blue.
Keywords :
autonomous aerial vehicles; game theory; military systems; particle swarm optimisation; predator-prey systems; PP-PSO; air military operation; attacking force Red; defense force Blue; dynamic game theory; dynamic task assignment problem; mixed Nash equilibrium; multiple UCAV air combat; multiple unmanned combat aerial vehicles; predator-prey particle swarm optimization approach; Atmospheric modeling; Force; Games; Nash equilibrium; Particle swarm optimization; Predator prey systems; Nash equilibrium; Unmanned combat aerial vehicle (UCAV); air combat; game theory; particle swarm optimization (PSO); predator-prey;
Journal_Title :
Automatica Sinica, IEEE/CAA Journal of
DOI :
10.1109/JAS.2015.7032901