Finding Optimal Strategy for Static Games by Using Genetic Algorithm

In this paper, one of the artificial intelligence algorithms was used, which is the genetic algorithm that is based on the application of innovative concepts including selection, crossover and mutation. A genetic algorithm was suggested for the static games to find the equilibrium and to estimate the asymptotic least squares was suggested, and we obtain good results in comparison with the ordinary algorithm. The application of the genetic algorithm on static games led to finding several solutions according to the times of simulations that represent the optimum solution ( the optimum value of equilibrium).