Suppr超能文献

基于主体的大脑建模:通过分层协同进化实现

Agent-based brain modeling by means of hierarchical cooperative coevolution.

作者信息

Maniadakis Michail, Trahanias Panos

机构信息

Foundation for Science and Technology, Hellas University of Crete, Greece.

出版信息

Artif Life. 2009 Summer;15(3):293-336. doi: 10.1162/artl.2009.Trahanias.007.

Abstract

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.

摘要

我们致力于开发受大脑启发的模型,这些模型将被嵌入机器人系统以支持其认知能力。我们引入了一种新颖的基于智能体的协同进化计算框架,用于对脑区集合进行建模。具体而言,采用自组织智能体结构来表示脑区。为了支持智能体的设计,我们引入了一种分层协作协同进化(HCCE)方案,该方案有效地指定了自主但协作的系统组件的结构细节。基于HCCE的设计机制能够研究模型在损伤条件下的性能,从而促进了设计过程。有趣的是,HCCE还提供了一种一致的机制来(如有必要)重新配置智能体的结构,便于后续的建模工作。实现的模型被嵌入到模拟机器人中以支持其行为能力,这也证明了所提出的计算框架的有效性。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验