%0 Conference Paper %1 phon-amnuaisuk:evows07 %A Phon-Amnuaisuk, Somnuk %A Law, Edwin Hui Hean %A Ho, Chin Kuan %B Applications of Evolutionary Computing, EvoWorkshops2007: EvoCOMNET, EvoFIN, EvoIASP, EvoInteraction, EvoMUSART, EvoSTOC, EvoTransLog %C Valencia, Spain %D 2007 %E Giacobini, Mario %E Brabazon, Anthony %E Cagnoni, Stefano %E Di Caro, Gianni A. %E Drechsler, Rolf %E Farooq, Muddassar %E Fink, Andreas %E Lutton, Evelyne %E Machado, Penousal %E Minner, Stefan %E O'Neill, Michael %E Romero, Juan %E Rothlauf, Franz %E Squillero, Giovanni %E Takagi, Hideyuki %E Uyar, A. Sima %E Yang, Shengxiang %I Springer Verlag %K Automatic Features Map, Music Self-Organising algorithms, generation genetic programming, %P 557--566 %R doi:10.1007/978-3-540-71805-5_61 %T Evolving Music Generation with SOM-fitness Genetic Programming %V 4448 %X Most real life applications have huge search spaces. Evolutionary Computation provides an advantage in the form of parallel explorations of many parts of the search space. In this report, Genetic Programming is the technique we used to search for good melodic fragments. It is generally accepted that knowledge is a crucial factor to guide search. Here, we show that SOM can be used to facilitate the encoding of domain knowledge into the system. The SOM was trained with music of desired quality and was used as fitness functions. In this work, we are not interested in music with complex rules but with simple music employed in computer games. We argue that this technique provides a flexible and adaptive means to capture the domain knowledge in the system.

@inproceedings{phon-amnuaisuk:evows07, abstract = {Most real life applications have huge search spaces. Evolutionary Computation provides an advantage in the form of parallel explorations of many parts of the search space. In this report, Genetic Programming is the technique we used to search for good melodic fragments. It is generally accepted that knowledge is a crucial factor to guide search. Here, we show that SOM can be used to facilitate the encoding of domain knowledge into the system. The SOM was trained with music of desired quality and was used as fitness functions. In this work, we are not interested in music with complex rules but with simple music employed in computer games. We argue that this technique provides a flexible and adaptive means to capture the domain knowledge in the system.}, added-at = {2008-06-19T17:46:40.000+0200}, address = {Valencia, Spain}, author = {Phon-Amnuaisuk, Somnuk and Law, Edwin Hui Hean and Ho, Chin Kuan}, biburl = {https://www.bibsonomy.org/bibtex/26a0824d093e433664222e63fa570b674/brazovayeye}, booktitle = {Applications of Evolutionary Computing, EvoWorkshops2007: {EvoCOMNET}, {EvoFIN}, {EvoIASP}, {EvoInteraction}, {EvoMUSART}, {EvoSTOC}, {EvoTransLog}}, doi = {doi:10.1007/978-3-540-71805-5_61}, editor = {Giacobini, Mario and Brabazon, Anthony and Cagnoni, Stefano and {Di Caro}, Gianni A. and Drechsler, Rolf and Farooq, Muddassar and Fink, Andreas and Lutton, Evelyne and Machado, Penousal and Minner, Stefan and O'Neill, Michael and Romero, Juan and Rothlauf, Franz and Squillero, Giovanni and Takagi, Hideyuki and Uyar, A. Sima and Yang, Shengxiang}, interhash = {a5c9d72ac84aa1515f243c3ebd69d16b}, intrahash = {6a0824d093e433664222e63fa570b674}, isbn13 = {978-3-540-71804-8}, keywords = {Automatic Features Map, Music Self-Organising algorithms, generation genetic programming,}, month = {11-13 April}, notes = {EvoWorkshops2007}, pages = {557--566}, publisher = {Springer Verlag}, series = {LNCS}, timestamp = {2008-06-19T17:49:30.000+0200}, title = {Evolving Music Generation with {SOM}-fitness Genetic Programming}, volume = 4448, year = 2007 }