The CARINA Metacognitive Architecture
| Autor: | Catriona Kennedy, Manuel F. Caro, Dalia Patricia Madera, Adan A. Gomez, Darsana P. Josyula |
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| Rok vydání: | 2019 |
| Předmět: |
Cognitive science
Computer science media_common.quotation_subject Cognitive computing Intelligent decision support system Metacognition 02 engineering and technology Cognitive architecture Task (project management) Human-Computer Interaction 03 medical and health sciences 0302 clinical medicine Artificial Intelligence 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Architecture 030217 neurology & neurosurgery Software Autonomy media_common |
| Zdroj: | International Journal of Cognitive Informatics and Natural Intelligence. 13:71-90 |
| ISSN: | 1557-3966 1557-3958 |
| Popis: | Metacognition has been used in artificial intelligence to increase the level of autonomy of intelligent systems. However, the design of systems with metacognitive capabilities is a difficult task due to the number and complexity of processes involved. The main objective of this article is to introduce a novel metacognitive architecture for monitoring and control of reasoning failures in artificial intelligent agents. CARINA metacognitive architecture is based on precise definitions of structural and functional elements of metacognition as defined in the MISM meta-model. CARINA can be used to implement real-world cognitive agents with the capability for introspective monitoring and meta-level control. Introspective monitoring detects reasoning failure (for example, when expectation is violated). Metacognitive control selects strategies to recover from failures. The article demonstrates a CARINA implementation of reasoning failure detection and recovery in an intelligent tutoring system called FUNPRO. |
| Databáze: | OpenAIRE |
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