Graph explorer

Computational Metacognition

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.

8 nodes7 linksoverview previewComputational Metacognition
8 nodes7 links
Computational Metacognition8 visible / 8 total nodes / 22 links
Co-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipCo-authorshipAuthorshipAuthorshipAuthorshipAuthorshipTopic signalAuthorshipAuthorshipWComputational Metacognitionpreprint / 2022AMichael CoxResearcherAZahiduddin MohammadResearcherASravya KondrakuntaResearcherAVentaksamapth Raja Gogi...ResearcherTArtificial Intelligence22915 worksADustin DannenhauerResearcherAOthalia LarueResearcher
PaperSignal 107 links

Computational Metacognition

preprint / 2022

Open