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Doubting What to Eat: A Computational Model for Food Choice Using Different Valuing Perspectives

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Neural Information Processing (ICONIP 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9950))

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Abstract

In this paper a computational model for the decision making process of food choices is presented that takes into account a number of aspects on which a decision can be based, for example, a temptation triggered by the food itself, a desire for food triggered by being hungry, valuing by the expected basic satisfaction feeling, and valuing by the expected goal satisfaction feeling.

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Author information

Authors and Affiliations

  1. Behavioural Informatics Group, Vrije Universiteit Amsterdam, De Boelelaan 1081, 1081 HV, Amsterdam, The Netherlands

    Altaf H. Abro & Jan Treur

Authors
  1. Altaf H. Abro
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  2. Jan Treur
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Corresponding author

Correspondence to Altaf H. Abro .

Editor information

Editors and Affiliations

  1. The University of Tokyo , Tokyo, Japan

    Akira Hirose

  2. Kobe University , Kobe, Japan

    Seiichi Ozawa

  3. Okinawa Institute of Science and Technology Graduate University, Onna, Japan

    Kenji Doya

  4. Nara Institute of Science and Technology , Ikoma, Japan

    Kazushi Ikeda

  5. Kyungpook National University , Daegu, Korea (Republic of)

    Minho Lee

  6. Chinese Academy of Sciences , Beijing, China

    Derong Liu

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Abro, A.H., Treur, J. (2016). Doubting What to Eat: A Computational Model for Food Choice Using Different Valuing Perspectives. In: Hirose, A., Ozawa, S., Doya, K., Ikeda, K., Lee, M., Liu, D. (eds) Neural Information Processing. ICONIP 2016. Lecture Notes in Computer Science(), vol 9950. Springer, Cham. https://doi.org/10.1007/978-3-319-46681-1_20

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  • DOI: https://doi.org/10.1007/978-3-319-46681-1_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46680-4

  • Online ISBN: 978-3-319-46681-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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