提出意识理论中的循环结构如何提升智能体实时适应能力
Hypothesis on the Functional Advantages of the Selection-Broadcast Cycle Structure: Global Workspace Theory and Dealing with a Real-Time World
- 将选择-广播循环结构作为认知核心，实现动态思维自适应
- 在实时环境中展现经验积累与即时响应双重优势
- 适合构建无需预设规则的通用型机器人与AI系统
本文探讨了全局工作空间理论（GWT）提出的“选择-广播循环”结构的功能优势，尤其关注其在人工智能与机器人面对动态、实时场景时的应用潜力。以往研究多孤立分析选择与广播过程，本文强调二者协同循环带来的三重优势：动态思维适应、基于经验的适应以及即时实时适应。该结构支持复杂环境下的自主决策与持续学习，展现出在无监督、动态环境中实现稳健通用智能的前景，为发展可应对真实世界任务的鲁棒性人工智能与机器人系统提供了新方向。
原文摘要 · Abstract (English)
This paper discusses the functional advantages of the Selection-Broadcast Cycle structure proposed by Global Workspace Theory (GWT), inspired by human consciousness, particularly focusing on its applicability to artificial intelligence and robotics in dynamic, real-time scenarios. While previous studies often examined the Selection and Broadcast processes independently, this research emphasizes their combined cyclic structure and the resulting benefits for real-time cognitive systems. Specifically, the paper identifies three primary benefits: Dynamic Thinking Adaptation, Experience-Based Adaptation, and Immediate Real-Time Adaptation. This work highlights GWT's potential as a cognitive architecture suitable for sophisticated decision-making and adaptive performance in unsupervised, dynamic environments. It suggests new directions for the development and implementation of robust, general-purpose AI and robotics systems capable of managing complex, real-world tasks.
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