Publication 2013 Issue No. 2 - April-June Abstract - HED: A Computational Model of Affective Adaptation and Emotion Dynamics
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HED: A Computational Model of Affective Adaptation and Emotion Dynamics
April-June 2013 (vol. 4 no. 2)
pp. 197-210
 ASCII Text x John E. Steephen, "HED: A Computational Model of Affective Adaptation and Emotion Dynamics," IEEE Transactions on Affective Computing, vol. 4, no. 2, pp. 197-210, April-June, 2013.
 BibTex x @article{ 10.1109/T-AFFC.2013.2,author = {John E. Steephen},title = {HED: A Computational Model of Affective Adaptation and Emotion Dynamics},journal ={IEEE Transactions on Affective Computing},volume = {4},number = {2},issn = {1949-3045},year = {2013},pages = {197-210},doi = {http://doi.ieeecomputersociety.org/10.1109/T-AFFC.2013.2},publisher = {IEEE Computer Society},address = {Los Alamitos, CA, USA},}
 RefWorks Procite/RefMan/Endnote x TY - JOURJO - IEEE Transactions on Affective ComputingTI - HED: A Computational Model of Affective Adaptation and Emotion DynamicsIS - 2SN - 1949-3045SP197EP210EPD - 197-210A1 - John E. Steephen, PY - 2013KW - Adaptation modelsKW - Mathematical modelKW - Computational modelingKW - PsychologyKW - Differential equationsKW - Predictive modelsKW - AppraisalKW - dynamical systemKW - Affective adaptationKW - modeling human emotionKW - region-$(\beta)$ paradoxKW - temporal dynamicsVL - 4JA - IEEE Transactions on Affective ComputingER -
John E. Steephen, University of Hyderabad, Hyderabad
Affective adaptation is the process of weakening of the affective response of a constant or repeated affective stimulus by psychological processes. A modified exponentially weighted average computational model of affective adaptation, which predicts its time course and the resulting affective dynamics, is presented. In addition to capturing the primary features of affective adaptation, it is shown that the model is consistent with several previously reported characteristics of affective dynamics. For instance, the model shows that elicited emotion is determined by the position, displacement, velocity, and acceleration of the stimulus. It also demonstrates that affective after-reaction correlates positively with stimulus intensity and duration and that the duration-of-current-ownership, duration-of-prior-ownership, and time-elapsed-since-loss effects can be explained by it. The model exhibits the region-$(\beta)$ paradox that refers to the observation that stronger emotions sometimes abate faster than the weaker ones. The model also predicts that the proposed mechanisms underlying the paradox may have other effects on affective dynamics as well. Besides offering an explanation for the contradicting reports on emotion intensity-duration relationship, it is also proposed that adaptation processes activate quickly but deactivate slowly. Potential applications in affective computing as well as some new lines of empirical research are discussed.
Index Terms:
Adaptation models,Mathematical model,Computational modeling,Psychology,Differential equations,Predictive models,Appraisal,dynamical system,Affective adaptation,modeling human emotion,region-$(\beta)$ paradox,temporal dynamics
Citation:
John E. Steephen, "HED: A Computational Model of Affective Adaptation and Emotion Dynamics," IEEE Transactions on Affective Computing, vol. 4, no. 2, pp. 197-210, April-June 2013, doi:10.1109/T-AFFC.2013.2