%0 Journal Article %1 oai:inderscience.com:6616 %A Kamitani, Motoki %A Ae, Tadashi %D 2005 %I Inderscience Publishers %J International Journal of Technology, Policy and Management %K Markov agent, algorithms, composition, computation, evolutionary generation, genetic hidden interactive model, music partial prediction programming, sequence sequences. %N 4 %P 337--352 %R doi:10.1504/04.6616 %T Augmented interactive evolutionary computation for composition %U http://www.inderscience.com/link.php?id=6616 %V 4 %X we propose an augmented interactive evolutionary computation technique to generate a symbol sequence, which is composed of several partial sequences. We introduce two-levels of feedback mechanism for evaluations, where the inner cycle induces an evolution of prediction agent for evaluation realised by a hidden Markov model, and the outer cycle induces an interaction with the user by selecting the candidate generated by the prediction agent. We describe, first, the process of augmented interactive evolutionary computation, and discuss the cooperative generation of sequences, which affects an anticipatory effective creation of formed sequence such as a music score. Next, we show several experimental results, which provide the generation of partial sequences and formed sequence.

@article{oai:inderscience.com:6616, abstract = {we propose an augmented interactive evolutionary computation technique to generate a symbol sequence, which is composed of several partial sequences. We introduce two-levels of feedback mechanism for evaluations, where the inner cycle induces an evolution of prediction agent for evaluation realised by a hidden Markov model, and the outer cycle induces an interaction with the user by selecting the candidate generated by the prediction agent. We describe, first, the process of augmented interactive evolutionary computation, and discuss the cooperative generation of sequences, which affects an anticipatory effective creation of formed sequence such as a music score. Next, we show several experimental results, which provide the generation of partial sequences and formed sequence.}, added-at = {2008-06-19T17:35:00.000+0200}, author = {Kamitani, Motoki and Ae, Tadashi}, bibsource = {OAI-PMH server at www.inderscience.com}, biburl = {https://www.bibsonomy.org/bibtex/2e72cd06880eb15319944c345e553c16f/brazovayeye}, doi = {doi:10.1504/04.6616}, interhash = {3295f61466d7a0c304412c9a2af6fd1c}, intrahash = {e72cd06880eb15319944c345e553c16f}, issn = {1741-5292}, journal = {International Journal of Technology, Policy and Management}, keywords = {Markov agent, algorithms, composition, computation, evolutionary generation, genetic hidden interactive model, music partial prediction programming, sequence sequences.}, language = {eng}, month = {March~28}, note = {Special Issue on Developments in Decision Technologies}, notes = {http://www.inderscience.com/browse/index.php?journalID=28 Graduate School of Engineering, Hiroshima University, 1-4-1 Kagamiyama, Higashi-Hiroshima 739-8527, Japan. ' Graduate School of Engineering, Hiroshima University, 1-4-1 Kagamiyama, Higashi-Hiroshima 739-8527, Japan}, number = 4, oai = {oai:inderscience.com:6616}, pages = {337--352}, publisher = {Inderscience Publishers}, relation = {ISSN online: 1741-5292 ISSN print: 1468-4322 DOI: 10.1504/04.6616}, rights = {Inderscience Copyright}, source = {IJTPM (2004), Vol 4 Issue 4, pp 337 - 352}, timestamp = {2008-06-19T17:42:52.000+0200}, title = {Augmented interactive evolutionary computation for composition}, url = {http://www.inderscience.com/link.php?id=6616}, volume = 4, year = 2005 }