在通用认知模型中加入元认知，让系统能自我反思认知能力。
A Proposal to Extend the Common Model of Cognition with Metacognition
- 用工作记忆中的显式表征实现元认知推理
- 仅对原模型做最小结构扩展即可支持元认知
- 适合研究意识、自我监控的人工智能系统
通用认知模型（CMC）为类人心智的认知架构提供了抽象的结构与处理描述。本文提出一种统一方法，将元认知整合进CMC。我们认为，元认知涉及对代理认知能力与过程的显式表征在工作记忆中的推理。该方案利用了CMC已有的认知能力，仅在工作记忆的结构与信息内容上做了最小扩展。我们展示了该框架下元认知的若干实例，证明其可行性与简洁性。
原文摘要 · Abstract (English)
The Common Model of Cognition (CMC) provides an abstract characterization of the structure and processing required by a cognitive architecture for human-like minds. We propose a unified approach to integrating metacognition within the CMC. We propose that metacognition involves reasoning over explicit representations of an agent's cognitive capabilities and processes in working memory. Our proposal exploits the existing cognitive capabilities of the CMC, making minimal extensions in the structure and information available within working memory. We provide examples of metacognition within our proposal.
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