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

机译：在脑竞技场中行动的代理人的分层协同进化

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摘要

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.
机译：最近，许多脑启发性模型已用于尝试支持人造生物的认知能力。在本文中，我们介绍了一个促进这些工作的计算框架，强调了脑子结构的协同性能。具体来说，我们介绍了一个基于代理的大脑区域表示，以及一个分层的协同协同进化设计机制。考虑到大脑区域的特殊性及其合作表现，所提出的方法能够设计出受生物启发的认知系统。通过设计大脑启发的工作记忆使用模型，可以证明所提出方法的有效性。协同进化方案可增强代表所涉及的大脑区域的代理的协作，从而通过同一模型促进完成两个不同的任务。此外，我们调查了模型在病变情况下的性能，强调了代表大脑区域的药物的独特作用。已实现的模型嵌入到模拟的机器人平台中，以支持其认知和行为能力。

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