An Affective Utility Model of User Motivation for Counselling Dialogue Systems View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2017

AUTHORS

Zoraida Callejas , David Griol

ABSTRACT

Counselling dialogue systems are designed to help users to change and monitor their behaviours in order to achieve beneficial goals, such as the acquisition of healthy habits. To be effective, it is important that these systems include a model that accounts for the effort that users are investing to achieve the goals. However, most of the systems available nowadays carry out a naïve calculation based on the attained results, rather than on the reasons behind the successes or failures and their consequences for future user behaviour. In contrast to this, in this paper we propose a model that characterizes user motivation considering various aspects of psychological theories on subjective expected utility and attribution. Moreover, we provide a specification that allows carrying out calculations that replicate the users’ decision-making process considering its emotional implications. The model is general-purpose and can be employed in standard architectures to make interpretations that adapt to each user, thus fostering more flexible and personalized interactions. More... »

PAGES

86-97

References to SciGraph publications

  • 2005. Affective-Cognitive Learning and Decision Making: A Motivational Reward Framework for Affective Agents in AFFECTIVE COMPUTING AND INTELLIGENT INTERACTION
  • 2011-12. Predicting user mental states in spoken dialogue systems in APPLIED SIGNAL PROCESSING
  • 2011-06-08. Annotating Disengagement for Spoken Dialogue Computer Tutoring in NEW PERSPECTIVES ON AFFECT AND LEARNING TECHNOLOGIES
  • Book

    TITLE

    Future and Emerging Trends in Language Technology. Machine Learning and Big Data

    ISBN

    978-3-319-69364-4
    978-3-319-69365-1

    Author Affiliations

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-319-69365-1_7

    DOI

    http://dx.doi.org/10.1007/978-3-319-69365-1_7

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1092418856


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