Modelling robotic cognitive mechanisms by hierarchical cooperative CoEvolution

Abstract

The current work addresses the development of cognitive abilities in artificial organisms. In the proposed approach, neural network-based agent structures are employed to represent distinct brain areas. We introduce a Hierarchical Cooperative CoEvolutionary (HCCE) approach to design autonomous, yet collaborating agents. Thus, partial brain models consisting of many substructures can be designed. Replication of lesion studies is used as a means to increase reliability of brain model, highlighting the distinct roles of agents. The proposed approach effectively designs cooperating agents by considering the desired pre- and post- lesion performance of the model. In order to verify and assess the implemented model, the latter is embedded in a robotic platform to facilitate its behavioral capabilities. © Springer-Verlag Berlin Heidelberg 2006.