%0 Book Section %1 99evmus %A Todd, Peter M. %A Werner, Gregory M. %B Musical Networks: Parallel Distributed Perception and Performance %D 1999 %E Griffith, Niall %E Todd, Peter M. %I MIT Press %K algorithms, coevolution genetic music, programming, %P 313--340 %T Frankensteinian approaches to evolutionary music composition %U http://www-abc.mpib-berlin.mpg.de/users/ptodd/publications/99evmus/99evmus.pdf %X Victor Frankenstein sought to create an intelligent being imbued with the rules of civilized human conduct, who could further learn how to behave and possibly even evolve through successive generations into a more perfect form. Modern human composers similarly strive to create intelligent algorithmic music composition systems that can follow prespecified rules, learn appropriate patterns from a collection of melodies, or evolve to produce output more perfectly matched to some aesthetic criteria. Here we review recent efforts aimed at each of these three types of algorithmic composition. We focus particularly on evolutionary methods, and indicate how monstrous many of the results have been. We present a new method that uses coevolution to create linked artificial music critics and music composers, and describe how this method can attach the separate parts of rules, learning, and evolution together into one coherent body. %@ 0-262-07181-9

@incollection{99evmus, abstract = {Victor Frankenstein sought to create an intelligent being imbued with the rules of civilized human conduct, who could further learn how to behave and possibly even evolve through successive generations into a more perfect form. Modern human composers similarly strive to create intelligent algorithmic music composition systems that can follow prespecified rules, learn appropriate patterns from a collection of melodies, or evolve to produce output more perfectly matched to some aesthetic criteria. Here we review recent efforts aimed at each of these three types of algorithmic composition. We focus particularly on evolutionary methods, and indicate how monstrous many of the results have been. We present a new method that uses coevolution to create linked artificial music critics and music composers, and describe how this method can attach the separate parts of rules, learning, and evolution together into one coherent body.}, added-at = {2008-06-19T17:46:40.000+0200}, author = {Todd, Peter M. and Werner, Gregory M.}, biburl = {https://www.bibsonomy.org/bibtex/2703f0a69fb23b159c22dd602af2ce219/brazovayeye}, booktitle = {Musical Networks: Parallel Distributed Perception and Performance}, editor = {Griffith, Niall and Todd, Peter M.}, interhash = {d9fc2f0ecf021dcdcf41f6f78daf9446}, intrahash = {703f0a69fb23b159c22dd602af2ce219}, isbn = {0-262-07181-9}, keywords = {algorithms, coevolution genetic music, programming,}, notes = {Survey. Mentions \cite{Spector:1994:ccaga} and \cite{Spector:1995:irdms} cf Lee Spector's email to GP list Wed, 27 Apr 2005 21:21:24 EDT}, pages = {313--340}, publisher = {MIT Press}, size = {pages}, timestamp = {2008-06-19T17:53:10.000+0200}, title = {Frankensteinian approaches to evolutionary music composition}, url = {http://www-abc.mpib-berlin.mpg.de/users/ptodd/publications/99evmus/99evmus.pdf}, year = 1999 }