Distributed brain modelling by means of hierarchical collaborative coevolution

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 collaborative coevolutionary (HCCE) approach to design autonomous, yet cooperating 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 HCCE is appropriately designed to support systematic modelling of brain structures, able to reproduce biological lesion data. 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.