ConBreO: a music performance rendering system using hybrid approach of IEC and automated evolution

Created by W.Langdon from gp-bibliography.bib Revision:1.8010

@InProceedings{Tanji:2010:gecco,

• author = "Makoto Tanji and Hitoshi Iba",
• title = "{ConBreO}: a music performance rendering system using hybrid approach of {IEC} and automated evolution",
• booktitle = "GECCO '10: Proceedings of the 12th annual conference on Genetic and evolutionary computation",
• year = "2010",
• editor = "Juergen Branke and Martin Pelikan and Enrique Alba and Dirk V. Arnold and Josh Bongard and Anthony Brabazon and Juergen Branke and Martin V. Butz and Jeff Clune and Myra Cohen and Kalyanmoy Deb and Andries P Engelbrecht and Natalio Krasnogor and Julian F. Miller and Michael O'Neill and Kumara Sastry and Dirk Thierens and Jano {van Hemert} and Leonardo Vanneschi and Carsten Witt",
• isbn13 = "978-1-4503-0072-8",
• pages = "1275--1282",
• keywords = "genetic algorithms, genetic programming, Real world applications",
• month = "7-11 " # jul,
• organisation = "SIGEVO",
• address = "Portland, Oregon, USA",
• DOI = "doi:10.1145/1830483.1830711",
• publisher = "ACM",
• publisher_address = "New York, NY, USA",
• abstract = "This paper presents an IEC (Interactive Evolutionary Computation) system named ConBreO to render expressive music performance using Genetic Programming. The central problem of IEC is the limitation of number of fitness evaluations because of user fatigue. In the system, we introduce two support techniques for IEC. The first one is a hybrid approach of IEC and automated evolution which allows the system to evolve both of IEC and automated evolution. The second one is the selective presentation which selects a new individual to be evaluated by the user based on its expected improvement of fitness. Using the system, obtained expression rule won an award at a performance rendering contest which evaluates computer systems generating expressive musical performances. Our experiment shows that the selective presentation reduces the number of fitness evaluations required to construct the fitness prediction model and prevents the system evaluating unfruitful individuals.",
• notes = "Also known as \cite{1830711} GECCO-2010 A joint meeting of the nineteenth international conference on genetic algorithms (ICGA-2010) and the fifteenth annual genetic programming conference (GP-2010)",

}

Genetic Programming entries for Makoto Tanji Hitoshi Iba

Citations