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A Flexible Scheme to Model the Cognitive Influence on Emotions in Autonomous Agents

A Flexible Scheme to Model the Cognitive Influence on Emotions in Autonomous Agents

Sergio Castellanos, Luis-Felipe Rodríguez
Copyright: © 2018 |Volume: 12 |Issue: 4 |Pages: 20
ISSN: 1557-3958|EISSN: 1557-3966|EISBN13: 9781522543053|DOI: 10.4018/IJCINI.2018100105
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MLA

Castellanos, Sergio, and Luis-Felipe Rodríguez. "A Flexible Scheme to Model the Cognitive Influence on Emotions in Autonomous Agents." IJCINI vol.12, no.4 2018: pp.81-100. http://doi.org/10.4018/IJCINI.2018100105

APA

Castellanos, S. & Rodríguez, L. (2018). A Flexible Scheme to Model the Cognitive Influence on Emotions in Autonomous Agents. International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), 12(4), 81-100. http://doi.org/10.4018/IJCINI.2018100105

Chicago

Castellanos, Sergio, and Luis-Felipe Rodríguez. "A Flexible Scheme to Model the Cognitive Influence on Emotions in Autonomous Agents," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI) 12, no.4: 81-100. http://doi.org/10.4018/IJCINI.2018100105

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Abstract

Autonomous agents (AAs) are designed to embody the natural intelligence by incorporating cognitive mechanisms that are applied to evaluate stimuli from an emotional perspective. Computational models of emotions (CMEs) implement mechanisms of human information processing in order to provide AAs for a capability to assign emotional values to perceived stimuli and implement emotion-driven behaviors. However, a major challenge in the design of CMEs is how cognitive information is projected from the architecture of AAs. This article presents a cognitive model for CMEs based on appraisal theory aimed at modeling AAs' interactions between cognitive and affective processes. The proposed scheme explains the influence of AAs' cognition on emotions by fuzzy membership functions associated to appraisal dimensions. The computational simulation is designed in the context of an integrative framework to facilitate the development of CMEs, which are capable of interacting with cognitive components of AAs. This article presents a case study and experiment that demonstrate the functionality of the proposed models.

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