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The CARINA Metacognitive Architecture

The CARINA Metacognitive Architecture

Manuel Fernando Caro, Darsana P. Josyula, Dalia Patricia Madera, Catriona M. Kennedy, Adán A. Gómez
Copyright: © 2019 |Volume: 13 |Issue: 4 |Pages: 20
ISSN: 1557-3958|EISSN: 1557-3966|EISBN13: 9781522564591|DOI: 10.4018/IJCINI.2019100104
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MLA

Caro, Manuel Fernando, et al. "The CARINA Metacognitive Architecture." IJCINI vol.13, no.4 2019: pp.71-90. http://doi.org/10.4018/IJCINI.2019100104

APA

Caro, M. F., Josyula, D. P., Madera, D. P., Kennedy, C. M., & Gómez, A. A. (2019). The CARINA Metacognitive Architecture. International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), 13(4), 71-90. http://doi.org/10.4018/IJCINI.2019100104

Chicago

Caro, Manuel Fernando, et al. "The CARINA Metacognitive Architecture," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI) 13, no.4: 71-90. http://doi.org/10.4018/IJCINI.2019100104

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Abstract

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.

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