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Inferring user goals from personality and behavior in a causal model of user affect

Published: 12 January 2003 Publication History

Abstract

We present a probabilistic model, based on Dynamic Decision Networks, to assess user affect from possible causes of emotional arousal. The model relies on the OCC cognitive theory of emotions and is designed to assess student affect during the interaction with an educational game. A key element of applying the OCC theory to assess user affect is knowledge of user goals. Thus, in this paper we focus on describing how our model infers these goals from user personality traits and interaction behavior. In particular, we illustrate how we iteratively defined the structure and parameters for this part of the model by using both empirical data collected through Wizard of Oz experiments and relevant psychological findings

References

[1]
Ball, G. and J. Breeze, Emotion and Personality in a Conversational Agent, in Embodied Conversational Agents, J. Cassel, et al., (Eds.). 2000, The MIT Press. p. 189--219.
[2]
Buntine, W., A guide to the literature on learning graphical models. IEEE Transactions on Knowledge and Data Engineering, 1996. 8(195--210.).
[3]
Conati, C. and X. Zhou. Modeling Students Emotions from Cognitive Appraisal in Educational Games. in ITS 2002, 6th International Conf on Intelligent Tutoring Systems. 2002. Biarritz, France.
[4]
Costa, P.T. and R.R. McCrae, Four ways five factors are basic. Personality and Individual Differences 1, 1992. 13: p. 653--665.
[5]
de Vicente, A. and H. Pain. Informing the detection of the students' motivational state: an empirical study. in ITS 2002, 6th International Conf on Intelligent Tutoring Systems. 2002. Biarritz, France.
[6]
Dean, T. and K. Kanazawa, A Model for Reasoning about Persistence and Causation. Computational Intelligence, 1989. 5(3): p. 142--150.
[7]
Del Soldato, T. and B. du Boulay, Implementation of motivational tactics in tutoring systems. Journal of Artificial Intelligence in Education, 1995. 6(4)
[8]
Elliot, C. Using the affective reasoner to support social simulations. in Proc. of the 13th Annual Joint Confrence on Artificial Intelligence. 1993. Chambery, France,: Morgan Kaufmann.
[9]
Elliott, C., J. Rickel, and J. Lester, Lifelike Pedagogical Agents and Affective Computing: An Exploratory Synthesis, in Artificial Intelligence Today, Lecture Notes in Computer Science 1600, M. Wooldridge and M. Veloso, (Eds.). 1999, Springer Verlag. p. 195--212.
[10]
Goldberg, L.R., The development of markers of the Big Five factor structure. Psychological Assessment, 1992. 4: p. 26--42.
[11]
Graziano, W.G., L.A. Jensen-Campbell, and J.F. Finch, The Self as a Mediator Between Personality and Adjustment. Journal of Personality and Social Psychology, 1997. 73: p. 392-404.
[12]
Healy, J. and R. Picard. SmartCar: Detecting Driver Stress. in 15th International Conf on Pattern Recognition. 2000. Barcelona, Spain.
[13]
Heckerman, D., A tutorial on learning with Bayesian networks, in Learning in Graphical Models, Jordan.M., (Ed.). 1998.
[14]
Hudlicka, E. and M. McNeese, Assessment of User Affective and Belief States for Interface Adaptation: Application to an Air Force Pilot Task. User Modeling and User-Adapted Interaction, 2002. 12(1): p. 1--47.
[15]
Kaapor, A., S. Mota, and R. Picard. Toward a learning companion that recognizes affect. in AAAI Fall Symposium: Emotional and Intelligent 2, the tangled knot of social cognition. 2001: AAAI Press.
[16]
Murray, C. and K. VanLehn. DT Tutor: A decision-theoretic dynamic approach for optimal selection of tutorial actions. in ITS 2000. 2000. Montreal, Canada.
[17]
Ortony, A., G.L. Clore, and A. Collins, The cognitive structure of emotions. 1988: Cambridge University Press.
[18]
Picard, R., Affective Computing. 1997, Boston: MIT Press.
[19]
Vyzas, E. and R. Picard. Offline and Online Recognition of Emotion Expression from Physiological Data. in Workshop on Emotion-Based Agent Architectures, 3rd International Confrence on Autonomous Agents. 1999. Seattle, Wa.

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cover image ACM Conferences
IUI '03: Proceedings of the 8th international conference on Intelligent user interfaces
January 2003
344 pages
ISBN:1581135866
DOI:10.1145/604045
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 12 January 2003

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Author Tags

  1. affective computing
  2. dynamic decision networks
  3. educational games
  4. user modeling

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