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

Altaf H. Abro, Jan Treur

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

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.
Original languageEnglish
Title of host publicationNeural Information Processing
Subtitle of host publication23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16–21, 2016, Proceedings
EditorsAkira Hirose, Seiichi Ozawa, Kenji Doya, Minho Lee, Derong Liu
Place of PublicationKyoto, Japan
PublisherSpringer
Pages164-174
Number of pages11
Volume9950 LNCS
ISBN (Print)978-3-319-46680-4
DOIs
Publication statusPublished - 2016
Event23rd International Conference on Neural Information Processing, ICONIP 2016 - Kyoto, Japan
Duration: 16 Oct 201621 Oct 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9950 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference23rd International Conference on Neural Information Processing, ICONIP 2016
CountryJapan
CityKyoto
Period16/10/1621/10/16

Keywords

  • Computational model
  • Desire
  • Food choice
  • Hebbian learning

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