Hierarchical Cooperative CoEvolution Facilitates the Redesign of Agent-Based Systems.

The current work addresses the problem of redesigning brain-inspired artificial cognitive systems in order to gradually enrich them with advanced cognitive skills. In the proposed approach, properly formulated neural agents are employed to represent brain areas. A cooperative coevolutionary method, with the inherent ability to co-adapt substructures, supports the design of agents. Interestingly enough, the same method provides a consistent mechanism to reconfigure (if necessary) the structure of agents, facilitating follow-up modelling efforts. In the present work we demonstrate partial redesign of a brain-inspired cognitive system, in order to furnish it with learning abilities. The implemented model is successfully embedded in a simulated robotic platform which supports environmental interaction, exhibiting the ability of the improved cognitive system to adopt, in real-time, two different operating strategies. [ABSTRACT FROM AUTHOR]