Modelling robotic cognitive mechanisms by hierarchical cooperative coevolution

Authors:
Michail Maniadakis;Panos Trahanias
Affiliations:
Inst. of Computer Science, Foundation for Research and Technology-Hellas, Heraklion, Crete, Greece;Department of Computer Science, University of Crete, Heraklion, Crete, Greece
Venue:
SETN'06 Proceedings of the 4th Helenic conference on Advances in Artificial Intelligence
Year:
2006

Citing 5
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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.