Toward a parallel genetic algorithm approach based on collective intelligence for combinatorial optimization problems

This paper addresses collective intelligence routes used in artificial life. Preliminary results are used to optimize the performance of genetic algorithms. Due to interested in the behaviour oriented artificial intelligence, specific attention is placed on the biological phenomena that reveals something about collective intelligence. Then, we propose a parallel reinforced search algorithm for the GA that use a collective memory of the better structural changes in the individuals through the generations, in order to use that information like trace of search.