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Formalizing emotion concepts within a Bayesian model of theory of mind

Author(s)
Saxe, Rebecca R.; Houlihan, Sean Dae
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Creative Commons Attribution-NonCommercial-NoDerivs License http://creativecommons.org/licenses/by-nc-nd/4.0/
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Abstract
Sensitivity to others’ emotions is foundational for many aspects of human life, yet computational models do not currently approach the sensitivity and specificity of human emotion knowledge. Perception of isolated physical expressions largely supplies ambiguous, low-dimensional, and noisy information about others’ emotional states. By contrast, observers attribute specific granular emotions to another person based on inferences of how she interprets (or ‘appraises’) external events in relation to her other mental states (goals, beliefs, moral values, costs). These attributions share neural mechanisms with other reasoning about minds. Situating emotion concepts in a formal model of people's intuitive theories about other minds is necessary to effectively capture humans’ fine-grained emotion understanding.
Date issued
2017-03
URI
https://hdl.handle.net/1721.1/125152
Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Journal
Current Opinion in Psychology
Publisher
Elsevier BV
Citation
Saxe, Rebecca, and Sean Dae Houlihan. “Formalizing Emotion Concepts within a Bayesian Model of Theory of Mind.” Current Opinion in Psychology 17 (October 2017): 15–21.
Version: Author's final manuscript
ISSN
2352-2518
2352-250X

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