Estimation of Influence of Each Variable on User's Evaluation in Interactive Evolutionary Computation

Ryohei Funaki, Kentaro Sugimoto, Junichi Murata

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Recently, interactive evolutionary computation (IEC) has been extensively applied in those systems that recommend objects, such as images and sounds, to users based on their preference. If an IEC user's evaluation criteria are clearly known, they can be utilized for acceleration of IEC, merchandise development, and creativity support for designers. It is difficult to collect a large volume of evaluation data for their analysis because an IEC user cannot repeat the evaluation so many times. Therefore, the technique proposed in this study adopts paired comparison-based interactive differential evolution (IDE) to ease the burden of users, and it will extract the user evaluation criteria through less number of evaluation steps. These techniques estimate the user evaluation criteria using the distribution of solutions because IDE does not receive the evaluation values from its user. Techniques are proposed that estimate, through the IEC processes, the degree of influence of each variable on the evaluation by any given user. During the simulations, the proposed methods are evaluated on test problems.

Original languageEnglish
Title of host publication2018 9th International Conference on Awareness Science and Technology, iCAST 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages167-174
Number of pages8
ISBN (Electronic)9781538658260
DOIs
Publication statusPublished - Oct 31 2018
Event9th International Conference on Awareness Science and Technology, iCAST 2018 - Fukuoka, Japan
Duration: Sept 19 2018Sept 21 2018

Publication series

Name2018 9th International Conference on Awareness Science and Technology, iCAST 2018

Other

Other9th International Conference on Awareness Science and Technology, iCAST 2018
Country/TerritoryJapan
CityFukuoka
Period9/19/189/21/18

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Human-Computer Interaction
  • Information Systems and Management
  • Experimental and Cognitive Psychology
  • Social Psychology
  • Communication

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