Computational modeling of emotion: Toward improving the inter-and intradisciplinary exchange

Rainer Reisenzein, Eva Hudlicka, Mehdi Dastani, Jonathan Gratch, Koen Hindriks, Emiliano Lorini, John Jules Ch Meyer

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

The past years have seen increasing cooperation between psychology and computer science in the field of computational modeling of emotion. However, to realize its potential, the exchange between the two disciplines, as well as the intradisciplinary coordination, should be further improved. We make three proposals for how this could be achieved. The proposals refer to: 1) systematizing and classifying the assumptions of psychological emotion theories; 2) formalizing emotion theories in implementation-independent formal languages (set theory, agent logics); and 3) modeling emotions using general cognitive architectures (such as Soar and ACT-R), general agent architectures (such as the BDI architecture) or general-purpose affective agent architectures. These proposals share two overarching themes. The first is a proposal for modularization: deconstruct emotion theories into basic assumptions; modularize architectures. The second is a proposal for unification and standardization: Translate different emotion theories into a common informal conceptual system or a formal language, or implement them in a common architecture.

Original languageEnglish
Article number6517842
Pages (from-to)246-266
Number of pages21
JournalIEEE Transactions on Affective Computing
Volume4
Issue number3
DOIs
Publication statusPublished - 31 Oct 2013
Externally publishedYes

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Keywords

  • affective computing
  • agent logics
  • cognitive architectures
  • Computational emotion modeling
  • emotion theories
  • theory formalization

Cite this

Reisenzein, R., Hudlicka, E., Dastani, M., Gratch, J., Hindriks, K., Lorini, E., & Meyer, J. J. C. (2013). Computational modeling of emotion: Toward improving the inter-and intradisciplinary exchange. IEEE Transactions on Affective Computing, 4(3), 246-266. [6517842]. https://doi.org/10.1109/T-AFFC.2013.14