Using evolving agents to critique subjective music compositions

Chuen Tsai Sun, Ji Lung Hsieh, Chung Yuan Huang

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

Abstract

The authors describe a recommender model that uses intermediate agents to evaluate a large body of subjective data according to a set of rules and make recommendations to users. After scoring recommended items, agents adapt their own selection rules via interactive evolutionary computing to fit user tastes, even when user preferences undergo a rapid change. The model can be applied to such tasks as critiquing large numbers of music or written compositions. In this paper we use musical selections to illustrate how agents make recommendations and report the results of several experiments designed to test the model's ability to adapt to rapidly changing conditions yet still make appropriate decisions and recommendations.

Original languageEnglish
Title of host publication2006 International Conference on Computational Intelligence and Security, ICCIAS 2006
PublisherIEEE Computer Society
Pages474-480
Number of pages7
ISBN (Print)1424406056, 9781424406050
DOIs
Publication statusPublished - 2006 Jan 1
Event2006 International Conference on Computational Intelligence and Security, ICCIAS 2006 - Guangzhou, China
Duration: 2006 Oct 32006 Oct 6

Publication series

Name2006 International Conference on Computational Intelligence and Security, ICCIAS 2006
Volume1

Other

Other2006 International Conference on Computational Intelligence and Security, ICCIAS 2006
CountryChina
CityGuangzhou
Period06/10/306/10/6

ASJC Scopus subject areas

  • Computer Science(all)
  • Control and Systems Engineering

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    Sun, C. T., Hsieh, J. L., & Huang, C. Y. (2006). Using evolving agents to critique subjective music compositions. In 2006 International Conference on Computational Intelligence and Security, ICCIAS 2006 (pp. 474-480). [4072133] (2006 International Conference on Computational Intelligence and Security, ICCIAS 2006; Vol. 1). IEEE Computer Society. https://doi.org/10.1109/ICCIAS.2006.294180