Three level hierarchical decision making model with GA

In this paper we propose a numerical algorithm able to describe the Stackelberg strategy for a multi level hierarchical 3-person game via genetic algorithm evolution process. There is only one player for each hierarchical level: an upper level leader (player L0), an intermediate level leader (player L1) who acts as a follower for L0 and as a leader for the lower level player (player F) that is the sole actual follower of the game. We present a computational result via genetic algorithm approach. The idea of the Stackelberg- GA is to bring together genetic algorithms and Stackelberg strategy in order to process a genetic algorithm to build the Stackelberg strategy. Any player acting as a follower makes his decision at each step of the evolutionary process, playing a simple optimisation problem whose solution is supposed to be unique. An application to an Authority-Provider-User (APU) model in the context of wireless networks is discussed. The algorithm convergence is illustrated by means of some test cases.