基于全局工作空间理论的机器人认知架构
PDF下载 (134)HUANG Wenjie,CANGELOSI Angelo,CHELLA Antonio.基于全局工作空间理论的机器人认知架构[J].宁波大学学报(理工版),2025,38(2):49-58.DOI:10.20098/j.cnki.1001-5132.2024.1112
HUANG Wenjie,CANGELOSI Angelo,CHELLA Antonio.Global workspace theory-based cognitive architecture for robots[J].Journal of Ningbo University(Natural Science & Engineering Edition),2025,38(2):49-58.DOI:10.20098/j.cnki.1001-5132.2024.1112
| Title: | Global workspace theory-based cognitive architecture for robots |
| 作者: | HUANG Wenjie, CANGELOSI Angelo, CHELLA Antonio |
| Author(s): | HUANG Wenjie, CANGELOSI Angelo, CHELLA Antonio |
| 关键词: | 全局工作空间理论; 认知架构; 渐进; 生物启发式认知架构 |
| Keywords: | Global Workspace Theory; cognitive architecture; incremental; biologically inspired cognitive architecture |
| 分类号: | TP18 |
| DOI: | 10.20098/j.cnki.1001-5132.2024.1112 |
| 文献标识码: | A |
| 摘要: | 采用适用于神经科学的全局工作空间理论开发有意识的认知架构. 基于这一架构实现了不同的认知要素, 使得全局工作空间理论与人脑工作机制的兼容性得以增强. 从注意力、记忆和学习机制这些针对智能系统的研究主题开始进行探讨, 并对相关实验进行总结. 随后讨论了如何基于这三个基本要素及其相互关系研究认知机器人开发这一新主题. 这些工作为认知机器人认知架构的未来长期发展提供了基础. 此外, 采用渐进式研究路线用以上述架构的实现, 这与生物启发式认知架构的研究路线图相一致. |
| Abstract: | This paper adopts the Global Workspace Theory as a neuro-scientifically plausible theory for developing conscious cognitive architecture. The Global Workspace Theory’s compatibility with the working mechanisms underneath human brains is enhanced by the implementation of different cognitive features based on this framework. Amongst the topics in the literature for intelligent systems, we start with attention, memory and learning mechanisms, and corresponding experiments are summarized here. We also discuss how other topics of cognitive robotics could be developed based on these three basic components, and their correlations. This provides a foundation for future long-term development of cognitive architectures of cognitive robots. The research in this paper follows the incremental research pathway for the architecture implementation, which is consistent with the Biologically Inspired Cognitive Architecture roadmap. |
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| 备注/Memo: | Received date: 2024−11−09. JOURNAL OF NINGBO UNIVERSITY ( NSEE ): http://journallg.nbu.edu.cn/ Foundation item: Supported by the European Union’s Horizon Europe research and innovation program (101120727 - PRIMI). Biography: HUANG Wenjie, research associate, specializing in: machine learning & robotics. Email: wenjie.huang@manchester.ac.uk *Corresponding author: CANGELOSI Angelo, professor, specializing in: machine learning & robotics. Email: angelo.cangelosi@manchester.ac.uk 宁波大学学报(理工版)网址:http://journallg.nbu.edu.cn/ |