Agent-Based Brain Modeling by Means of Hierarchical Cooperative Coevolution

摘要

We address the development of brain-inspired models that will be embedded in robotic systems to support their cognitive abilities. We introduce a novel agent-based coevolutionary computational framework for modeling assemblies of brain areas. Specifically, self-organized agent structures are employed to represent brain areas. In order to support the design of agents, we introduce a hierarchical cooperative coevolutionary (HCCE) scheme that effectively specifies the structural details of autonomous, yet cooperating system components. The design process is facilitated by the capability of the HCCE-based design mechanism to investigate the performance of the model in lesion conditions. Interestingly, HCCE also provides a consistent mechanism to reconfigure (if necessary) the structure of agents, facilitating follow-up modeling efforts. Implemented models are embedded in a simulated robot to support its behavioral capabilities, also demonstrating the validity of the proposed computational framework.