Modelling Robotic Cognitive Mechanisms by Hierarchical Cooperative CoEvolution

The current work addresses the development of cognitive abilities in artiflcial organisms. In the proposed approach, neural network- based agent structures are employed to represent distinct brain areas. We introduce a Hierarchical Cooperative CoEvolutionary (HCCE) ap- proach to design autonomous, yet collaborating agents. Thus, partial brain models consisting of many substructures can be designed. Repli- cation of lesion studies is used as a means to increase reliability of brain model, highlighting the distinct roles of agents. The proposed approach efiectively 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.