让AI具备自我反思能力，更像人类地处理信息。
Metacognition in Content-Centric Computational Cognitive C4 Modeling
- 用内容驱动的认知模型构建可自我反思的AI
- 结合神经符号方法拓展机器人认知能力
- 针对大模型短板提出新发展方向
为了让AI代理能够模拟人类行为，必须使其能感知、有意义地解释、存储并使用关于世界、自身及其他代理的大量信息。元认知是这些过程不可或缺的组成部分。本文简要介绍面向下一代AI代理的内容中心型计算认知（C4）建模；回顾了罗切斯特理工学院LEIA（语言赋能智能代理）实验室长期开展的C4代理研究；讨论当前基于神经符号处理模型拓展LEIA认知能力至认知机器人应用的工作；并勾勒未来发展方向，旨在克服当前主流大语言模型方法中被低估的局限性。
原文摘要 · Abstract (English)
For AI agents to emulate human behavior, they must be able to perceive, meaningfully interpret, store, and use large amounts of information about the world, themselves, and other agents. Metacognition is a necessary component of all of these processes. In this paper, we briefly a) introduce content-centric computational cognitive (C4) modeling for next-generation AI agents; b) review the long history of developing C4 agents at RPI's LEIA (Language-Endowed Intelligent Agents) Lab; c) discuss our current work on extending LEIAs' cognitive capabilities to cognitive robotic applications developed using a neuro symbolic processing model; and d) sketch plans for future developments in this paradigm that aim to overcome underappreciated limitations of currently popular, LLM-driven methods in AI.
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