论文标题
计算元认知
Computational Metacognition
论文作者
论文摘要
计算元认知代表了综合人工系统中高阶推理的认知系统观点，该观点旨在利用人工智能中的人工元认知和元策划方法来利用思想。关键特征是在智能系统中声明代表并监视认知活动的痕迹，以管理认知本身的表现。然后，认知的改善会导致行为和绩效的改善。我们用一种名为MIDCA的认知架构中的代理实现来说明这些概念，并在解决问题中显示了元认知的价值。结果说明了计算元认知如何通过通过元级目标操作和学习来改变认知来提高性能。
Computational metacognition represents a cognitive systems perspective on high-order reasoning in integrated artificial systems that seeks to leverage ideas from human metacognition and from metareasoning approaches in artificial intelligence. The key characteristic is to declaratively represent and then monitor traces of cognitive activity in an intelligent system in order to manage the performance of cognition itself. Improvements in cognition then lead to improvements in behavior and thus performance. We illustrate these concepts with an agent implementation in a cognitive architecture called MIDCA and show the value of metacognition in problem-solving. The results illustrate how computational metacognition improves performance by changing cognition through meta-level goal operations and learning.
