Hierarchical Co-evolution of Cooperating Agents Acting in the Brain-Arena

Recently, many brain-inspired models have been used in attempts to support the cognitive abilities of artificial organisms. In this article, we introduce a computational framework to facilitate these efforts, emphasizing the cooperative performance of brain substructures. Specifically, we introduce an agent-based representation of brain areas, together with a hierarchical cooperative co-evolutionary design mechanism. The proposed methodology is capable of designing biologically inspired cognitive systems , considering both the specialties of brain areas and their cooperative performance. The effectiveness of the proposed approach is demonstrated by designing a brain-inspired model of working memory usage. The co-evolutionary scheme enforces the cooperation of agents representing the involved brain areas, facilitating the accomplishment of two different tasks by the same model. Furthermore, we investigate the performance of the model in lesion conditions, highlighting the distinct roles of agents representing brain areas. The implemented model is embedded in a simulated robotic platform to support its cognitive and behavioral capabilities.