Evolving multiple sensory-motor controllers based on cellular neural network

There has been extensive work to construct an optimal neural network for controlling a mobile robot by evolutionary approaches such as genetic algorithm, genetic programming, and so on. However, evolutionary approaches have a difficulty to obtain the controller that conducts complex and general behaviors. In order to overcome this short-coming, we propose a method of combining several evolved modules by a rule-based approach. The multi-modules integration method can make complex and general behaviors by combining several modules evolved or programmed to do simple behavior. Experimental results show the potential of the multi-modules integration method as a sophisticated technique to make the evolved neural network to do complex and general behaviors.