A Study of Genetic Programming on Cooperative Model for an Ant Colony

Abstract

A cooperative model is the action strategy in which every individual cooperates with others in a team. Thus, the better cooperative model the team has, the higher performance it has. However, every individual in the team can not detect all state of others. It only detects the change of the surroundings, and all individuals in the team are act independently. So, it is difficult to find an efficient cooperative model by human being. The genetic programming (GP) can program automatically by simulating the evolutionary mechanism and process on computers. When a program evolves using the GP technique, an efficient program often can be generated for solving a particular problem that the human being doesn't understand in detail how to solve it. So, in this research, we try use GP to evolve the cooperative model for the ant colony under both the single program architecture and the multi-agent architecture. Then, ants can efficiently transport the food to the nest under the generated model. It is proved that the GP technique can be used to evolve an efficient cooperative model. This research not only can be used to related research, but also can be applied to develop more complex cooperative models such as the cooperative models for robots and cooperative learning model