EEGS: A Transparent Model of Emotions
November 04, 2020 Β· Declared Dead Β· π arXiv.org
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Authors
Suman Ojha, Jonathan Vitale, Mary-Anne Williams
arXiv ID
2011.02573
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.MA,
cs.RO
Citations
3
Venue
arXiv.org
Last Checked
4 months ago
Abstract
This paper presents the computational details of our emotion model, EEGS, and also provides an overview of a three-stage validation methodology used for the evaluation of our model, which can also be applicable for other computational models of emotion. A major gap in existing emotion modelling literature has been the lack of computational/technical details of the implemented models, which not only makes it difficult for early-stage researchers to understand the area but also prevents benchmarking of the developed models for expert researchers. We partly addressed these issues by presenting technical details for the computation of appraisal variables in our previous work. In this paper, we present mathematical formulas for the calculation of emotion intensities based on the theoretical premises of appraisal theory. Moreover, we will discuss how we enable our emotion model to reach to a regulated emotional state for social acceptability of autonomous agents. We hope this paper will allow a better transparency of knowledge, accurate benchmarking and further evolution of the field of emotion modelling.
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