Using evolving agents to critique subjective music compositions

Chuen Tsai Sun, Ji Lung Hsieh, Chung Yuan Huang*

*Corresponding author for this work

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


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 publicationComputational Intelligence and Security - International Conference, CIS 2006, Revised Selected Papers
PublisherSpringer Verlag
Number of pages11
ISBN (Print)9783540743767
Publication statusPublished - 2007
Externally publishedYes
EventInternational Conference on Computational Intelligence and Security, CIS 2006 - Guangzhou, China
Duration: 2006 Nov 32006 Nov 6

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4456 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceInternational Conference on Computational Intelligence and Security, CIS 2006


  • Adaptive agent
  • Content-based filtering
  • Critiquing subjective data
  • Interactive evolutionary computing
  • Music recommender system

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


Dive into the research topics of 'Using evolving agents to critique subjective music compositions'. Together they form a unique fingerprint.

Cite this