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Towards the construction of computational models of emotions from the perspective of a software systemCognitive Systems Research10.1016/j.cogsys.2022.12.003
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Influences of cognitive appraisal and individual characteristics on citizens’ perception and emotion in urban environment: Model development and virtual reality experimentJournal of Environmental Psychology10.1016/j.jenvp.2024.102309

An Interoperable Framework for Computational Models of Emotion

Enrique Osuna, Sergio Castellanos, Jonathan Hernando Rosales, Luis-Felipe Rodríguez

Source Title: International Journal of Cognitive Informatics and Natural Intelligence (IJCINI)16(1)

ISSN: 1557-3958|EISSN: 1557-3966|EISBN13: 9781683180197|DOI: 10.4018/IJCINI.296257

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MLA

Osuna, Enrique, et al. "An Interoperable Framework for Computational Models of Emotion." IJCINI vol.16, no.1 2022: pp.1-15. http://doi.org/10.4018/IJCINI.296257

APA

Osuna, E., Castellanos, S., Rosales, J. H., & Rodríguez, L. (2022). An Interoperable Framework for Computational Models of Emotion. International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), 16(1), 1-15. http://doi.org/10.4018/IJCINI.296257

Chicago

Osuna, Enrique, et al. "An Interoperable Framework for Computational Models of Emotion," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI) 16, no.1: 1-15. http://doi.org/10.4018/IJCINI.296257

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Abstract

Computational models of emotion (CMEs) are software systems designed to emulate specific aspects of the human emotions process. The underlying components of CMEs interact with cognitive components of cognitive agent architectures to produce realistic behaviors in intelligent agents. However, in contemporary CMEs, the interaction between affective and cognitive components occurs in ad-hoc manner, which leads to difficulties when new affective or cognitive components should be added in the CME. This paper presents a framework that facilitates taking into account in CMEs the cognitive information generated by cognitive components implemented in cognitive agent architectures. The framework is designed to allow researchers define how cognitive information biases the internal workings of affective components. This framework is inspired in software interoperability practices to enable communication and interpretation of cognitive information and standardize the cognitive-affective communication process by ensuring semantic communication channels used to modulate affective mechanisms of CMEs