In this paper a numerical procedure based on a genetic algorithm (GA) evolution process is given to compute a Stackelberg solution for a hierarchical n+1-person game. There is a leader player who enounces a decision before the others, and the rest of players (followers) take into account this decision and Solve a Nash equilibrium problem. So there is a two-level game between the leader and the followers, called Stackelberg–Nash problem. 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. In the lower level, the followers make their decisions simultaneously at each step of the evolutionary process, playing a so called Nash game between themselves. The use of a multimodal genetic algorithm allows to find multiple Stackelberg strategies at the upper level. In this model the uniqueness of the Nash equilibrium at the lower-level problem has been supposed. The algorithm convergence is illustrated by means of several test cases.
A Hierarchical Multi-modal Hybrid Stackelberg-Nash GA for a Leader with Multiple Followers Game / D'Amato, Egidio; Daniele, Elia; Mallozzi, Lina; G., Petrone; Tancredi, Simone. - STAMPA. - Springer Proceedings in Mathematics & Statistics, Vol. 20:(2012), pp. 267-280.
A Hierarchical Multi-modal Hybrid Stackelberg-Nash GA for a Leader with Multiple Followers Game
D'AMATO, EGIDIO;DANIELE, ELIA;MALLOZZI, LINA;TANCREDI, SIMONE
2012
Abstract
In this paper a numerical procedure based on a genetic algorithm (GA) evolution process is given to compute a Stackelberg solution for a hierarchical n+1-person game. There is a leader player who enounces a decision before the others, and the rest of players (followers) take into account this decision and Solve a Nash equilibrium problem. So there is a two-level game between the leader and the followers, called Stackelberg–Nash problem. 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. In the lower level, the followers make their decisions simultaneously at each step of the evolutionary process, playing a so called Nash game between themselves. The use of a multimodal genetic algorithm allows to find multiple Stackelberg strategies at the upper level. In this model the uniqueness of the Nash equilibrium at the lower-level problem has been supposed. The algorithm convergence is illustrated by means of several test cases.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.