bibliography of genetic algorithms in arts and music

8/10/2019 Bibliography of Genetic Algorithms in Arts and Music

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An Indexed Bibliography of Genetic

Algorithms in Arts and Musiccompiled by

Jarmo T. Alander

Department of Electrical and Energy Engineering: Automation

University of Vaasa P.O. Box 700, FIN-65101 Vaasa, Finlandphone: +358-6-324 8444, fax: +358-6-324 8467

Report Series No. 94-1-ART (Updated 2014/05/06 11:37 )

available at http://www.uva.fi/~TAU/reports/report94-1/gaARTbib.pdf



Copyright c 1994-2013 Jarmo T. Alander

Cover image: c2010 Anssi Jantti, All rights reserved.GP producing graphics [1].

Trademarks

Product and company names listed are trademarks or trade names of their respective companies.

Warning

While this bibliography has been compiled with the utmost care, the editor takes no responsibility forany errors, missing information, the contents or quality of the references, nor for the usefulness and/orthe consequences of their application. The fact that a reference is included in this publication does notimply a recommendation. The use of any of the methods in the references is entirely at the user’s ownresponsibility. Especially the above warning applies to those references that are marked by trailing ’†’ (or’*’), which are the ones that the editor has unfortunately not had the opportunity to read. An abstractwas available of the references marked with ’*’.



Contents

1 Preface 1

1.1 Your contributions erroneous or missing? . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.1.1 How to cite this report? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.2 How to get this report via Internet? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21.3 Acknowledgement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

2 Introduction 4

3 Statistical summaries 53.1 Publication type . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53.2 Annual distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53.3 Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63.4 Authors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63.5 Geographical distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83.6 Conclusions and future . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

4 Indexes 9

4.1 Books . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94.2 Journal articles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94.3 Theses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

4.3.1 PhD theses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

4.3.2 Master’s theses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104.4 Report series . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104.5 Patents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104.6 Authors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114.7 Subject index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144.8 Annual index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174.9 Geographical index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

5 Permuted title index 19

Bibliography 29

Appendixes 41

A Abbreviations 41

B Bibliography entry formats 42

i



ii



Chapter 1

Preface

“ Living organism are consummate problem solvers. They exhibit a versatilitythat puts the best computer programs to shame. ”

John H. Holland, [2]

The material of this bibliography has been extracted from the genetic algorithm bibliography [3], whichwhen this report was compiled (May 6, 2014) contained 22162 items and which has been collected fromseveral sources of genetic algorithm literature including Usenet newsgroup comp.ai.genetic and thebibliographies [4, 5, 6, 7]. The following index periodicals and databases have been used systematically

• A: International Aerospace Abstracts: Jan. 1995 – Sep. 1998

• ACM: ACM Guide to Computing Literature: 1979 – 1993/4

• BA: Biological Abstracts: July 1996 - Aug. 1998

• CA: Computer Abstracts: Jan. 1993 – Feb. 1995

• CCA: Computer & Control Abstracts: Jan. 1992 – Dec. 1999 (except May -95)

• ChA: Chemical Abstracts: Jan. 1997 - Dec. 2000

• CTI: Current Technology Index Jan./Feb. 1993 – Jan./Feb. 1994

• DAI: Dissertation Abstracts International: Vol. 53 No. 1 – Vol. 56 No. 10 (Apr. 1996)

• EEA: Electrical & Electronics Abstracts: Jan. 1991 – Apr. 1998

• EI A: The Engineering Index Annual: 1987 – 1992

• EI M: The Engineering Index Monthly: Jan. 1993 – Apr. 1998 (except May 1997)

• Esp@cenet patents – Apr. 2002

• IEEE: IEEE and IEE Journals – Fall 2002

• N: Scientific and Technical Aerospace Reports: Jan. 1993 - Dec. 1995 (except Oct. 1995)

• NASA NASA ADS www bibliography database: – Dec. 2002

• P: Index to Scientific & Technical Proceedings: Jan. 1986 – Dec 1999 (except Nov. 1994)

• PA: Physics Abstracts: Jan. 1997 – June 1999

• PubMed: National Library of Medicine Jan. 2000 – Oct. 2000

• SPIE Web The International Society for Optical Engineering – June 2002

1



2 Genetic algorithms in arts and music

1.1 Your contributions erroneous or missing?

The bibliography database is updated on a regular basis and certainly contains many errors and incon-sistences. The editor would be glad to hear from any reader who notices any errors, missing information,articles etc. In the future a more complete version of this bibliography will be prepared for the geneticalgorithms in arts and music research community and others who are interested in this rapidly growingarea of genetic algorithms.

When submitting updates to the database, paper copies of already published contributions are pre-ferred. Paper copies (or ftp ones) are needed mainly for indexing. We are also doing reviews of differentaspects and applications of GAs where we need as complete as possible collection of GA papers. Please,do not forget to include complete bibliographical information: copy also proceedings volume title pages,

journal table of contents pages, etc. Observe that there exists several versions of each subbibliography,therefore the reference numbers are not unique and should not be used alone in communi-

cation, use the key appearing as the last item of the reference entry instead.Complete bibliographical information is really helpful for those who want to find your contribution

in their libraries. If your paper was worth writing and publishing it is certainly worth to be referencedright in a bibliographical database read daily by GA researchers, both newcomers and established ones.

1.1.1 How to cite this report?

You can use the BiBTEX file GASUB.bib, which is available in our site lipas.uwasa.fi in directoryreports/report94-1 and contains records for GA subbibliographies for citing with LATEX/BibTEX.

1.2 How to get this report via Internet?

Versions of this bibliography are available via www from the following site:

media country site directory file web Finland lipas.uwasa.fi ~TAU/reports/report94-1 gaARTbib.pdf

The directory also contains some other indexed GA bibliographies shown in table B.1. In case you do

not find a proper one please let us know: it may be easy to tailor a new one.

1.3 Acknowledgement

The editor wants to acknowledge all who have kindly supplied references, papers and other informationon genetic algorithms in arts and music literature. At least the following GA researchers have alreadykindly supplied their complete autobibliographies and/or proofread references to their papers: DanAdler, Patrick Argos, Jarmo T. Alander, James E. Baker, Wolfgang Banzhaf, Helio J. C. Barbosa,Hans-Georg Beyer, Christian Bierwirth, Peter Bober Joachim Born, Ralf Bruns, I. L. Bukatova, ThomasBack, Chhandra Chakraborti, Nirupam Chakraborti, David E. Clark, Carlos A. Coello Coello, YuvalDavidor, Dipankar Dasgupta, Marco Dorigo, J. Wayland Eheart, Bogdan Filipic, Terence C. Fogarty,David B. Fogel, Toshio Fukuda, Hugo de Garis, Robert C. Glen, David E. Goldberg, Martina Gorges-

Schleuter, Hitoshi Hemmi, Vasant Honavar, Jeffrey Horn, Aristides T. Hatjimihail, Heikki HyotyniemiMark J. Jakiela, Richard S. Judson, Bryant A. Julstrom, Charles L. Karr, Akihiko Konagaya, AaronKonstam, John R. Koza, Kristinn Kristinsson, Malay K. Kundu, D. P. Kwok, Jouni Lampinen, JormaLaurikkala, Gregory Levitin, Carlos B. Lucasius, Timo Mantere, Michael de la Maza, John R. McDonnell,J. J. Merelo, Laurence D. Merkle, Zbigniew Michalewics, Melanie Mitchell, David J. Nettleton, VolkerNissen, Ari Nissinen, Tatsuya Niwa, Tomasz Ostrowski, Kihong Park, Jakub Podgorski, Timo Poranen,Nicholas J. Radcliffe, Colin R. Reeves, Gordon Roberts, David Rogers, David Romero, Sam Sandqvist,Ivan Santibanez-Koref, Marc Schoenauer, Markus Schwehm, Hans-Paul Schwefel, Michael T. Semertzidis,Davil L. Shealy, Moshe Sipper, William M. Spears, Donald S. Szarkowicz, El-Ghazali Talbi, MasahiroTanaka, Leigh Tesfatsion, Peter M. Todd, Marco Tomassini, Andrew L. Tuson, Kanji Ueda, Jari Vaario,



Acknowledgement 3

Gilles Venturini, Hans-Michael Voigt, Roger L. Wainwright, D. Eric Walters, James F. Whidborne, StefanWiegand, Steward W. Wilson, Xin Yao, Xiaodong Yin, and Ljudmila A. Zinchenko.

The editor also wants to acknowledge Elizabeth Heap-Talvela for her kind proofreading of the manuscriptof this bibliography and Tea Ollanketo and Sakari Kauvosaari for updating the database. Prof. TimoSalmi and the Computer Centre of University of Vaasa is acknowledged for providing and managing theonline web site lipas.uwasa.fi, where these indexed bibliographies are located since Summer 2012.



Chapter 2

Introduction

“Many scientist, possibly most scientist, just do science without thinking toomuch about it. They run experiments, make observations, show how certaindata conflict with more general views, set out theories, and so on. Periodically,however, some of us—scientists included—step back and look at what is goingon in science.”

David L., Hull, [8]

The table 2.1 gives the queries that have been used to extract this bibliography. The query system as wellas the indexing tools used to compile this report from the BiBTEX-database [9] have been implementedby the author mainly as sets of simple awk and gawk programs [10, 11].

string field class ,art, ANNOTE Art,art ANNOTE Artaesthetics ANNOTE Aesthetics,architecture ANNOTE Architecture music ANNOTE Musicanimation ANNOTE Cartoons

computer graphics ANNOTE Computer graphicsAudio JOURNAL Audio journal

Table 2.1: Queries used to extract this subbibliography from the source database.

You might also find bibliographies [12] containing references to image processing, [13] ontaining refer-ences to signal processing, and [14] containing references to computer aided design applications interesting.

4



Chapter 3

Statistical summaries

This chapter gives some general statistical sum-maries of genetic algorithms in arts and music lit-erature. More detailed indexes can be found inthe next chapter.

References to each class (c.f table 2.1) are listed

below:

• Aesthetics 3 references ([15]-[17])

• Architecture 12 references ([18]-[29])

• Art 33 references ([30]-[62])

• Audio journal 14 references ([63]-[76])

• Cartoons 16 references ([77]-[92])

• Computer graphics 60 references ([93]-

[151])

• Music 34 references ([152]-[185])

Observe that each reference is included (by thecomputer) only to one of the above classes (see thequeries for classification in table 2.1; the textualorder in the query gives priority for classes).

3.1 Publication type

This bibliography contains published contributions

including reports and patents. All unpublishedmanuscripts have been omitted unless acceptedfor publication. In addition theses, PhD, MScetc., are also included whether or not publishedsomewhere.

Table 3.1 gives the distribution of publicationtype of the whole bibliography. Observe that thenumber of journal articles may also include ar-ticles published or to be published in unknownforums.

type number of items

book 4section of a book 1part of a collection 1

journal article 62proceedings article 86report 4PhD thesis 6MSc thesis 2others 7total 173

Table 3.1: Distribution of publication type.

3.2 Annual distribution

Table 3.2 gives the number of genetic algorithmsin arts and music papers published annually. Theannual distribution is also shown in fig. 3.1. Theaverage annual growth of GA papers has been ap-proximately 40 % during late 70’s - early 90’s.

year items year items

1989 2 1990 31991 7 1992 41993 10 1994 171995 28 1996 201997 18 1998 111999 8 2000 62001 6 2002 10

2003 8 2004 02005 2 2006 42007 4 2008 32009 0 2010 12011 0 2012 1total 173

Table 3.2: Annual distribution of contributions.

5



Authors 7

1

10

100

1000number of papers(log scale)

1960 1970 1980 1990 2000 2010

year

Genetic algorithms in arts and music

2014/05/06

Figure 3.1: The number of papers applying ge-

netic algorithms in arts and music (•, N =174 ) and total GA papers (◦, N = 22162 ). Ob-serve that the last few years are most incompletein the database.




3.5 Geographical distribution

Table 3.5 gives the geographical distribution of authors, when the country of the author was known. Over80% of the references of the GA source database are classified by country.

2014/05/06 special comparison all country n % δ [%] ∆[%] N %

Total 166 100.00 20961 100.00United States 43 25.90 −0.90 −3 5618 26.80United Kingdom 27 16.27 +6.28 +63 2095 9.99Japan 18 10.84 −0.95 −8 2472 11.79Germany 16 9.64 +2.98 +45 1395 6.66Finland 12 7.23 +3.08 +74 870 4.15China 11 6.63 +1.38 +26 1100 5.25Spain 9 5.42 +3.35 +162 434 2.07Canada 5 3.01 +1.40 +87 337 1.61Portugal 4 2.41 +1.89 +363 110 0.52Taiwan 4 2.41 +0.17 +8 470 2.24Australia 3 1.81 −0.63 −26 511 2.44Hungary 3 1.81 +1.53 +546 59 0.28South Korea 3 1.81 −0.40 −18 464 2.21Cuba 2 1.20 +1.17 +3900 7 0.03France 2 1.20 −1.38 −53 541 2.58Austria 1 0.60 +0.00 +0 126 0.60Denmark 1 0.60 +0.31 +107 60 0.29Italy 1 0.60 −2.25 −79 598 2.85New Zealand 1 0.60 +0.45 +300 32 0.15Singapore 1 0.60 −0.21 −26 169 0.81Others 1 0.60 +0.50 +500 21 0.10

Table 3.5: The geographical distribution of the authors working on genetic algorithms in arts and music(n) compared (δ and ∆) to all authors in the field of GAs (N ). In the comparison column: δ % =%special −%all and ∆ = (1− nN Total

NnTotal)× 100%. ∆ is the relative (%) deviation from the expected number

of special papers. Observe that joint papers may have authors from several countries and that not allauthors have been attributed to a country.

3.6 Conclusions and future

The editor believes that this bibliography contains references to most genetic algorithms in arts andmusic contributions upto and including the year 1998 and the editor hopes that this bibliography couldgive some help to those who are working or planning to work in this rapidly growing area of geneticalgorithms.



Chapter 4

Indexes

4.1 Books

The following list contains all items classified asbooks.

Principia Evolvica, Simulierte Evolution mit Mathematica,[135]

Evolutionary Art and Computers, [57]

Evolving images, [53]

Illustrating Evolutionary Computation with Mathematica,[96]

total 4 books

4.2 Journal articlesThe following list contains the references to every

journal article included in this bibliography. Thelist is arranged in alphabetical order by the nameof the journal.

ACM SIGAPL APL Quote Quad, [32]

Appl. Math. Comput. (USA), [145]

Autom. Constr., [26]

Axis (UK), [88]

Build Environment, [27]

Communications of the ACM, [150]Complexity (USA), [29]

Complexity International, [172]

Computer Graphics, [49]

Computer Music Journal, [156]

Computer Physics Communications, [147]

Computer-Aided Design, [36]

Computers in Chemical Engineering, [142]

Connect. Science, [39]

Digit. Creat. (UK), [137]

Engineering Applications of Artificial Intelligence, [31]

Ethology and Sociobiology, [95]

Forma, [111]Graphical Models, [98]

Helsingin Sanomat, [59]

IBM asiaa, [61]

IBM Journal of Research & Development, [99]

IBM Systems Journal, [45]

IEEE Transaction on Visualization and Computer Graph-ics, [103]

IEEE Transactions on Circuits and Systems for Video Tech-nology, [34]

IEEE Transactions on Speech & Audio Processing, [75]

IEEE Transactions on Speech and Audio Processing, [64,

65, 67, 76]

IEEE Transactions on Systems, Man, and Cybernetics,[108]

IEEE Transactions on Systems, Man, and Cybernetics-PartC: Applications and Reviews, [32]

INFORMS J. Comput., [141]

Internet Today, [129]

J. New Music Res. (Netherlands), [40]

Journal of Audio Engineers Society, [63]

Journal of Computers and Graphics, [116]

Journal of the Audio Engineering Society, [68, 69, 70, 71,

72, 73, 74]

Journal of Visualization and Computer Animation, [56, 82]

Kybernetes, [162]

Laryngoscope, [15]

Lighting Research and Technology, [23, 24]

Microcomputers in Civil Engineering, [16]

Muhely (The Hungarian Journal of Modern Art), [62]

New Scientist, [46]

Pattern Recognition, [97]

Scandinavian Audiology, [66]

Scientific Computing World, [139]

9




SIGCSE Bulletin, [90]

The Journal of the Acoustical Society of America, [176, 177]

The Visual Computer, [52, 127]

Transactions of the Institute of Electronics, Information,and Communication Engineers D-II (Japan), [87,

146]

total 63 articles in 49 series

4.3 Theses

The following two lists contain theses, first PhDtheses and then Master’s etc. theses, arranged inalphabetical order by the name of the school.

4.3.1 PhD theses

Columbia University, [161]

Eotvos Lorand University, [104]

Harvard University, [77]

University of Erlanger-Nurnberg, [117]

University of Michigan, [67]

University of Surrey, [180]

total 6 thesis in 6 schools

4.3.2 Master’s theses

This list includes also “Diplomarbeit”, “Tech. Lic.

Theses”, etc.

Technische Hochschule Darmstadt, [110]

University of Industrial Arts Helsinki, [30]

total 2 thesis in 2 schools

4.4 Report series

The following list contains references to all pa-pers published as technical reports. The list isarranged in alphabetical order by the name of the

institute.

IBM, [54]

Max-Planck Intitut fur Informatik, [115]

University of Illinois at Urbana-Champaign, [153]

University of Vaasa, [43]

total 4 reports in 4 institutes

4.5 Patents

The following list contains the names of thepatents of genetic algorithms in arts and music.The list is arranged in alphabetical order by thename of the patent.

Data structure for system kitchen editing and designing,[20]

House design system using genetic algorithm, [21]

House design system using genetic algorithm, [18, 19]

Method and device for generating musical sound waveform,[184]

total 4 patents



Authors 11

4.6 Authors

The following list contains all genetic algorithms in arts and music authors and references to their knowncontributions.

Agah, Arvin, [32]

Agui, Takeshi, [87]

Ahn, Byung-Ha, [159]

Alander, Jarmo T., [1, 43]

Ala-Siuru, Pekka, [33]

Alfonseca, Manuel, [99]

Alfonso, Rafael Sanhez, [158, 160]

Anderson, Peter G., [175]

Angeline, Peter J., [132]

Aoki, A., [146]

Aoki, K., [125, 138]

Auramo, Yrjo, [66]

Ayers, L., [170, 176]

Bair, Alethea, [103]

Baker, Ellie, [38]

Baluja, Shumeet, [39]

Baum, Karl G., [105]

Beauchamp, James, [63, 156]

Bersano-Begey, Tommaso F., [178]

Beyer, Markus, [109, 110,112, 115]

Biles, J. A., [175]

Biles, John A., [167, 177]

Birchfield, David Andrew, [161]

Blanchet, C., [24]

Boccara, M., [84]

Branke, Jurgen, [17]

Brice, A. A., [142]

Bucher, Frank, [17]

Budiarto, Rahmat, [111]

Burton, A. R., [179]

Burton, Anthony Richard, [180]

Bustillo, Eduardo, [136]

Buxton, Bernard F., [80]

Byrne, J. A., [157]

Caldalda, J. J. Romero, [185]

Chan, San-Kuen, [72]

Chang, Seok C., [159]

Chen, Wen-Pin, [15]

Chen, Yeong-Chinq, [97]

Chetverikov, Dmitry, [101, 102]

Cheung, N.-M., [71]

Cho, Sung-Bae, [31]

Chou, Jyh-Rong, [36]

Clark, Sean, [129]

Coley, D. A., [27, 29]

Corcione, M., [23]

Cotta, Carlos, [106]

Crabb, J. A., [27]

Crochemore, D., [84, 86]

Daida, Jason M., [178]

Dainghaus, R., [122]

Dalhoum, Abdellatif Abu, [99]

de Vega, Francisco Fernandez, [163,164]

Dequn, Liang, [131]

Devcic, Zlatko, [15]

Ding, Lan, [28]

Dodgson, N., [92]

Dorado, J., [185]

dos Reis, Gustavo Miguel Jorge, [163,164]

Durant, E. A., [67]

Durant, Eric A., [67]

Eastman, Charles M., [26]

Ebner, Marc, [100]

Ekart, Aniko, [102]

Fernandez, Francisco, [165]

Fernandez de Vega, F., [106]

Ferreira, Aniıbal, [165]

Flaig, T., [122]

Fontana, L., [23]

Fovargue, A., [90]

Frade, Miguel, [106]

Franklin, M., [95]

Fujimura, Kikou, [127]

Fujimura, N., [125]

Fukunaga, Alex, [81]

Furuta, H., [16, 120]

Garigliano, Roberto, [116]

Geigel, Joe, [78]

Gero, John S., [28]

Gervautz, M., [130]

Gibson, P. M., [157]

Goldberg, David E., [152, 153, 154]

Graf, Jeanine, [119]

Greenwood, Garrison W., [75]

Griffiths, S., [88]

Gritz, Larry, [82, 89, 78]

Gustafson, Steven C., [148]

Hahn, James K., [82, 89]

Hahn, James, [78]

Haken, Lippold, [63, 156]

Hall, M. A., [171]

Hamer, R. D., [88]

Hamid, Mahmoud S., [34, 35]

Harvey, Neal R., [34]

Helguera, Marıa, [105]

Herdy, Michael, [42]

Hirose, A., [120]

Ho, Shinn-Ying, [97]

Hobden, A., [123]

Homaifar, Abdollah, [155]

Horner, Andrew B., [170, 40, 68,71, 72, 73, 176, 74, 152, 153, 154,63, 156]

Horner, Andrew, [64, 76]

Horowitz, Damon, [166]

House, Donald H., [103]

Hughes, P., [56]

Hung, Chia-Young, [37]

Hung, Fei-Kung, [37]

Hwu, Jiing-Yuan, [65]

Iba, Hitoshi, [79]

Itoh, Hidenori, [111]

Jackson, D., [90]



Authors 13

Traxler, C., [130]

Tsai, Hung-Cheng, [36, 37]

Tsutsumi, Kazutoshi, [25]

Tuson, Andrew, [181]

Veitch, J. A., [22, 24]

Ventrella, J., [41]

Vepsalainen, Marja-Leena, [61]

Verner, O. V., [141]

Viikki, Kati, [66]

Vladimirova, T., [179]

Vucic, Vedran, [62]

Wainwright, R. L., [141]

Wakaki, Hiromi, [79]

Wakefield, Gregory H., [67]

Ware, Colin, [103]

Watanabe, E., [16]

Wiggins, Geraint, [181, 182]

Williams, R. D., [88]

Winters, D., [29]

Wong, Brian J. F., [15]

Wong, Kit Po, [91]

Xuan, Yang, [131]

Yamada, Masashi, [111]

Yamamoto, Kenji, [140]

Yang, H. C., [151]

Yang, Yee-Hong, [98]

Yoshida, Toshiya, [184]

Yu, J. F., [151]

Yuen, J., [74]

Zhang, Y. G., [145]

total 172 articles by 264 differ-ent authors




4.7 Subject index

All subject keywords of the papers given by the editor of this bibliography are shown next.

acoustics, [176]

double frequency, [69]

drum, [172]

aesthetics, [17, 29]

bridge design, [16]

agents

communications, [162]

ecosystems, [162]

analysing GA

animation, [90]

animation, [47, 77, 78,81, 82, 83, 84, 85, 41, 87, 91]

animation

3D characters, [89]

CAL, [88]

cloth, [86]

computer graphics, [92]

application

computer graphics, [52, 53]

architecture, [27, 29, 18,19, 20, 21, 25]

aesthetics, [28]

CAD, [26]

illumination design, [22, 23, 24]

art, [44, 45, 46,48, 54, 49, 55, 56, 50, 51, 57, 47,52, 53, 59, 58, 60, 61, 62]

art

artificial life, [30]

bibliography, [43]

cartoons, [41]

color design, [36, 37]

colours, [42]

computer generated, [38, 39]

digital, [32]

fashion, [31]

movies, [34, 35]

music, [40]

review, [33]

artificial life, [59, 129]

trees, [145]

audiosynthesis, [74]

Avatar, [79]

bibliography

art, [43]

music, [43]

special, [43]

CAD, [108, 119, 101]

buildings, [26]

color design, [36, 37]

face, [15]

CD-ROM

graphics, [58]

chemistry

structural, [77]

chromosomes

polyploid, [96, 135]

classifier systems, [92]

clothes

design, [31]

color

combinations, [137]

color harmony, [36, 37]

colors

visualization, [105]

computational geometry, [100]

shape modeling, [128]

computer games

graphics, [106]

computer graphics, [44,45, 46, 48, 54, 49, 55, 56, 94, 50,57, 93, 47, 107, 108, 109, 111, 113,114, 58, 83, 117, 60, 119, 125, 127,132, 134, 17, 136, 139, 62, 147, 148,150, 151, 96, 97, 135, 32, 104]

computer graphics

animation, [79, 81]

art, [129]

color, [137, 105]

face, [95]

flowsheet drawing, [142]fractals, [116, 130, 131]

GP, [1]

graphs, [121, 143]

L-systems, [124, 149, 99]

labeling, [141]

lighting, [146]

Lindenmayer systems, [144]

photorealism, [101]

photorealistic, [102]

ray trace, [118]

ray tracing, [110, 112, 115]

redering, [122]

rendering, [110, 112, 115]

scene graphs, [100]

shading, [128]

stereo, [103]

superquadrics, [133, 140]

texture, [123]

texture generation, [98]

trees, [145]

computer graphics?, [120, 126, 138]control, [67]

motion, [82, 87]

design, [120]

fashion, [31]

display, [111]

dress

design, [31]

engineering

civil, [26, 16, 27, 25]

structural, [16]

esthetics

KANSEI, [25]

evolution

beauty, [95]

simulation, [117]

evolution strategies, [75, 96, 135]

interactive, [42]

Evolvica, [96, 135]



Subject index 15

expert systems, [66]

faces, [83]

FEM, [25]

acoustics, [172]

films

restoration, [34, 35]

filter

morphological, [34, 35]

fitness

aesthetics, [15]

interactive, [15]

fitness function

human, [95]

interactive, [31]

neural network, [175, 179]

fractals, [116, 130]

IFS, [131, 145]

L-systems, [99]

fuzzy systems, [122]

GALAPAGOS, [94]

genetic programming, [49, 50, 51,52, 53, 82, 123, 126, 89, 178, 147,96, 135]

genetic programming

computer graphics, [106, 1]

L-systems, [107]

music, [173]

geometry

polygonal approximation, [97]

grammars

music, [158, 160]

graphs

drawing, [121]

layout, [114]

rendering, [143]

rrawing, [17]

hearing aid, [67]

hybrid

neural networks, [180]

simulated annealing, [70]

iamging

stereo, [103]

illumination

design, [22, 23, 24]

image processing

color, [137]

fractals, [131]

image registration, [101, 102]

range image, [140]

registration, [104]

restoration, [34, 35]

shading, [133]

shape, [128]

synthetic, [32]

image registration

3D, [101, 102]

implementation

Connection Machine, [49]

Mathematica, [124, 96, 135]

industrial art, [31]

interactive, [94]

interactive design, [125]

interactive GA, [119]

Internet, [129]

inverse problems

fractals, [131]

L-System, [107]

L-systems, [93, 117, 126,134, 134, 147]

Latham, [59, 129]

layout design, [94, 108]

flowsheet, [142]

labels in maps, [141]

lighting, [125]

Lindenmayer systems, [96, 135]

machine learning, [114, 28]

mathematics

integration, [118]

medical imaging

visualization, [105]

medicine

neurology, [66]

plastic surgery, [15]

sensing, [67]

modulation

double frequency, [69]

music, [168, 169,170, 40, 69, 173, 175, 176, 180]

adaptive synthesis, [183]

analysis, [171]

bibliography, [43]

composing, [178]

composition, [155, 174,179, 181, 185, 158, 160, 161]

drum, [172]

electronic, [70, 74]

instruments, [68]

jazz, [167, 177]

jazz melodies, [182]

rhytms, [166]

synthesis, [163, 164]

tones, [63, 156, 72,72]

transcription, [165]

wavetables, [73]

music composition, [152, 153,154, 157]

music?, [162]

neural networks, [157, 87, 136]

fitness, [179]

training, [75]

optics

lighting design, [23]

ray tracing, [109]

optimization

global, [77]

parallel GA, [49]

parameter estimation

texture, [98]

patent, [184, 18, 19,20, 21]

pattern recognition, [65]

music, [159]

shape representation, [97]

physics

mechanics, [41]

placing, [141]

plants

artificial, [96, 135]

popular, [61, 129]




neural networks, [139]

rendering

sound, [78]

review

AI in art, [33]

artificial life, [30]

selection

interactive, [42]

sensing

hearing, [67]

sexual selection, [95]

shape design

roofs, [25]

wind turbine, [100]

signal processing, [68, 76, 64]

audio, [71, 73, 176]

modulation, [70]

music, [184, 163, 164]

sampling, [74]

speech, [65]

tones, [72]

sound, [162]

composition, [78]

superquadrics, [133, 140]

tomography

MR, [105]

PET, [105]

tutorial

animation, [80]

video tape, [48]

virtual reality, [122]

visualisation, [148]

visualization

palette design, [105]



Annual index 17

4.8 Annual index

The following table gives references to the contributions by the year of publishing.

1989, [44, 45]

1990, [46, 48, 54]1991, [152, 153, 154, 157, 49, 55, 56]

1992, [94, 50, 51, 57]

1993, [155, 63, 156, 93, 47, 77, 52, 53, 78, 95]

1994, [38, 81, 166, 107, 167, 108, 168, 109,110, 169, 111, 59, 39, 112, 113, 114, 115]

1995, [58, 170, 116, 26, 82, 83, 40, 117, 118,84, 60, 85, 41, 61, 16, 119, 120, 68, 86, 171, 87, 121, 122,88, 123, 124, 172, 43]

1996, [125, 69, 70, 42, 126, 127, 173, 128,129, 174, 130, 131, 132, 175, 133, 134, 71, 72, 73, 176]

1997, [17, 27, 136, 89, 137, 177, 90, 28, 74,138, 139, 178, 140, 141, 62, 179, 29, 75]

1998, [142, 76, 180, 143, 144, 181, 182, 183,184, 145, 146]

1999, [91, 185, 147, 92, 148, 149, 150, 151]

2000, [64, 65, 18, 30, 31, 19]

2001, [96, 66, 20, 97, 21, 135]

2002, [158, 67, 67, 22, 79, 32, 33, 159, 98, 160]

2003, [99, 80, 161, 162, 100, 23, 34, 35]

2005, [24, 101]

2006, [102, 103, 25, 104]

2007, [163, 36, 164, 37]

2008, [15, 105, 106]

2010, [1]

2012, [165]




4.9 Geographical index

The following table gives references to the contributions by country.

• Australia: [28, 9 1, 162]

• Austria: [130]

• Canada: [150, 9 6, 2 2, 9 8, 2 4]

• China: [131, 145, 151, 40, 71, 72, 73, 176, 74, 76, 64]

• Cuba: [121, 143]

• Denmark: [62]

• Finland: [78, 168, 59 , 60, 85, 61, 43, 183, 30 , 66, 33, 1]

• France: [86, 172]

• Germany: [93, 109, 110, 112, 115, 117, 118, 119, 122,124, 42, 134, 17, 147, 135, 100]

• Hungary: [101, 102, 104]

• Italy: [23]

• Japan: [79, 114, 16, 120, 68, 87, 125, 128, 133, 138, 140,184, 146, 18, 19, 20, 21, 25]

• New Zealand: [171]

• Singapore: [70]

• South Korea: [83, 3 1, 159]

• Spain: [136, 185, 158, 160, 99, 163, 164, 106, 165]

• Taiwan: [65, 97, 36, 37]

• United Kingdom: [44, 45, 46, 54, 157, 55, 56, 57, 47,116, 88, 123, 129, 27, 137, 90, 139, 179, 29, 142, 180,144, 181, 182, 92 , 80]

• United States: [48, 152, 153, 154, 49, 50, 51, 155, 63,156, 77, 52, 53, 95, 38, 81, 166, 167, 169, 39, 113, 58,26, 82, 41, 127, 173, 175, 177, 178, 141, 75, 148, 149,67, 3 2, 161, 34, 3 5, 103, 105]

• Unknown country: [111, 170, 6 9, 174, 89, 1 5]



Chapter 5

Permuted title index

The words of the titles of the articles are shown in the next table arranged in alphabetical order. Themost common words have been excluded. The key word is shown by a disk (•) in the title field with theexception that it is omitted when appearing as the first word of the title after shown keyword. The otherabbreviation used to compress titles are shown in appendix A.

[97] accurate An efficient evol. alg. for • polygonal approx-imation

[93] activity Patterns of cluster formation and evol. • inevolving L-syst.

[176] adaptive Common tone • tuning using GAs[183] additive Opt. • synthesis parameters with GAs and

self-organizing maps[16] aesthetic Appl. of GA to • design of bridge structures[29] – GA search efficacy in • product spaces[15] aesthetics Evolving attractive faces using morphing

technology and a GA: A new appr. to determining ideal facial•

[33] AI in contemporary (interactive)art[67] Aid Hearing • Fitting with GAs[105] algorithm-generated Evaluation of gen. • multivari-

ate color tables for the visualization of multimodal medicalfused data sets

[60] Alkavatko taideteoksetkin elaa? [Is art getting life?][64] amplitudes Low peak • for wavetable synthesis[81] animated Automatic cntr. of physically realistic • fig-

ures using EP[41] – Disney meets Darwin – the evol. of funny • figures[78] – Using physically-based models and GAs for functional

composition of sound signals, synchronized to • motion[91] Animating the evol. process of GAs[84] animation Building new tools for synthetic image • by

using evol. techniques[56] – Computer sculpture design and •

[80] – Evol. alg. in modeling and •

[86] – Evol. ident. of cloth • models[89] – Gen. prog. evol. of cntr. for 3-D character •

[77] – Global Opt. for Articulated Figures: Molecular Struc-ture Prediction and Motion Synthesis for •

[79] – Motion design of a 3D-CG avatar that uses humanoid•

[47] – The appl. of evol. and biological processes to computer

art and •

[90] – The use of • to explain GAs[88] – Three-dimensional colour image and • modelling for

CAL[70] annealing Automated parameter opt. for douple fre-

quency modulation synthesis using the gen. • alg.[69] – Automatic parameter opt. for double frequency mod-

ulation synthesis using the gen. • alg.[174] application GeNotator: An environment for investigat-

ing the • of GAs in computer assisted composition[156] – Machine tongues XVI. GAs and their • to FM matching

synthesis[16] • of GA to aesthetic design of bridge structures[120] • of GA to design of artificial ground

[31] • of interactive GA to fashion design[34] applications GA opt. of multidimensional grayscale

soft morphological filters with • in film archive restoration[47] – The • of evol. and biological processes to computer art

and animation[173] applied A grammar based gen. prog. technique • to

music generation[180] – A hybrid neuro-gen. pattern evol. syst. • to musical

composition[1] Applying GArphics - • GAs for generating graphics[110] Approximation der Rendering Equation durch Evol.

are Alg. en[67] approximations Efficient model fitting using a GA:

pole-zero • of HRTFs[34] archive GA opt. of multidimensional grayscale soft

morphological filters with appl. in film • restoration[60] art Alkavatko taideteoksetkin elaa? [Is • getting life?]

[55] – Artificial life or surreal •[57] – Evol. • and Computers[43] – Indexed Bibliography of GAs in • and Music[129] – Organic •

[47] – The appl. of evol. and biological processes to computer• and animation

[61] – Tietokonetaide on monien ilmioiden leikkauspiste[Computer •

[159] ART-1 Music recognition syst. using • and GA[82] articulated Gen. prog. for • figure motion[77] – Global Opt. for • Figures: Molecular Structure Pre-

diction and Motion Synthesis for Animation[120] artificial Appl. of GA to design of • ground[30] – Geneesys – katsaus kolmiulotteiseen keinoelamaan nyt

ja hahmotelma tulevaisuudesta [A Review of 3D • Life andOutline of its Future]

[124] – Gen. L-syst. prog. : breeding and evolving • flowerswith Mathematica

[145] – Lifelike • trees based on growth iterated function syst.

[49] • evol. for computer graphics[39] – Towards automated • evol. for computer-generated im-

ages[27] Artificial intelligence appr. to the prediction of nat.

lighting levels[85] Artificial life Keinoelamaa virtuaalitodellisuudessa –

hyttysia ja muita otokoita • in virtual reality – Gnats andother little creatures]

[150] Artificial life for computer graphics[55] • or surreal art?[59] artist Kaarmemaiset sykkyrat pyorivat, hajoavat ja

kulkevat itsensa lapi, Tietokonetaiteilija William Latham luoolioitaan evoluution saantojen avulla [Refers to works of com-puter • William Latham]

19




[62] arts Self-evolving • Organisms versus fetishes[174] assisted GeNotator: An environment for investigating

the appl. of GAs in computer • composition[36] association Automatic design support and image eval-

uation of two-coloured products using colour • and colour har-mony scales and GA

[15] attractive Evolving • faces using morphing technologyand a GA: A new appr. to determining ideal facial aesthetics

[171] attributed Sel. of • for modeling Bach chorales by aGA

[70] Automated parameter opt. for douple frequency mod-ulation synthesis using the gen. annealing alg.

[39] – Towards • artificial evol. for computer-generated im-ages

[163] automatic A novel appr. to • music transcription usingelectronic synthesis and GAs

[87] – An • GA-based construction of neural networks for mo-tion cntr. of virtual life

[164] – Electronic synthesis using GAs for • music transcrip-tion

[165] – Evol. alg. and • transcription of music[158, 160] • composition of music by means of grammatical

evol.[81] • cntr. of physically realistic animated figures using EP[36] • design support and image evaluation of two-coloured

products using colour association and colour harmony scalesand GA

[121] • graph drawing by gen. search[69] • parameter opt. for double frequency modulation syn-

thesis using the gen. annealing alg.[37] • product color design using gen. searching[108] Automating the layout of network diagrams with spec-

ified visual organization[79] avatar Motion design of a 3D-CG • that uses humanoid

animation[59] avulla Kaarmemaiset sykkyrat pyorivat, hajoavat ja

kulkevat itsensa lapi, Tietokonetaiteilija William Latham luoolioitaan evoluution saantojen • [Refers to works of computerartist William Latham]

[169] Bach in a box: The evol. of four part baroque harmonyusing the GA

[171] Bach Sel. of attributed for modeling • chorales by a GA[169] baroque Bach in a box: The evol. of four part • har-

mony using the GA[95] beauty Is • in the eye of the beholder[95] beholder Is beauty in the eye of the •

[43] Bibliography Indexed • of GAs in Art and Music[47] biological The appl. of evol. and • processes to com-

puter art and animation[92] blending Motion • using a CS[169] box Bach in a • The evol. of four part baroque harmony

using the GA[124] breeding Gen. L-syst. prog. : • and evolving artificial

flowers with Mathematica[16] bridge Appl. of GA to aesthetic design of • structures[25] buildings Roof shape generation method for • using

KANSEI evaluation rules[88] CAL Three-dimensional colour image and animation

modelling for •

[111] cat’s A • cradle string diagram display method based ona GA

[65] cepstrum GA-based noisy speech recognition usingtwo-dimensional •

[138] CG 3-D • lighting with an interactive GA[89] character Gen. prog. evol. of cntr. for 3-D • anima-

tion[171] chorales Sel. of attributed for modeling Bach • by a

GA[92] classifier Motion blending using a • syst.[86] cloth Evol. ident. of • animation models[93] cluster Patterns of • formation and evol. activity in

evolving L-syst.[147] coevolution Evol. and • of developmental prog.[37] color design Automatic product • using gen. searching[105] color tables Evaluation of GA-generated multivariate

• for the visualization of multimodal medical fused data sets[137] colour A two-stage evol. model for the computer-aided

design of • combinations[36] – Automatic design support and image evaluation of two-

coloured products using • association and colour harmonyscales and GA

[36] colour harmony Automatic design support and imageevaluation of two-coloured products using colour associationand • scales and GA

[88] colour image Three-dimensional • and animation mod-elling for CAL

[137] combinations A two-stage evol. model for thecomputer-aided design of colour •

[103] complex An appr. to the perceptual opt. of • visual-izations

[44] – FormSynth: The rule-based evol. of • forms from geo-metric primitives

[155] composes GA • music[178] composing Musica ex machina: • 16th-century coun-

terpoint with gen. prog. and symbiosis[180] composition A hybrid neuro-gen. pattern evol. syst.

appl. to musical •[158, 160] – Automatic • of music by means of grammatical

evol.[181] – Evol. methods for musical •[179] – GA utilising neural network fitness evaluation for mu-

sical •[152, 153, 154] – GAs and computer-assisted music •

[174] – GeNotator: An environment for investigating the appl.of GAs in computer assisted •

[157] – Neurogen, music • using GAs and cooperating neuralnetworks

[78] – Using physically-based models and GAs for functional• of sound signals, synchronized to animated motion

[185] compositor Gen. music •

[96] Computation Illustrating Evol. • with Mathematica[73] • and memory tradeoffs with multiple wavetable inter-

polation[137] computer-aided A two-stage evol. model for the • de-

sign of colour combinations[152, 153, 154] computer-assisted GAs and • music compo-

sition[39] computer-generated Towards automated artificial

evol. for • images[151] connection Optimized • of rational surface-based on

GAs[114] constraints Evol. learning of graph layout • from ex-

amples[87] construction An automatic GA-based • of neural net-

works for motion cntr. of virtual life[33] contemporary AI in • (interactive)art[87] control An automatic GA-based construction of neural

networks for motion • of virtual life[81] – Automatic • of physically realistic animated figures us-

ing EP[122] controlled A fuzzy • rendering syst. for virtual reality

syst. optimised by GAs[89] controllers Gen. prog. evol. of • for 3-D character

animation[157] cooperating Neurogen, music composition using GAs

and • neural networks[178] counterpoint Musica ex machina: composing 16th-

century • with gen. prog. and symbiosis[111] cradle A cat’s • string diagram display method based

on a GA[102] Creating photorealistic models by data fusion with GAs[113] creatures Evolving virtual •[85] – Keinoelamaa virtuaalitodellisuudessa – hyttysia ja

muita otokoita [Artificial life in virtual reality – Gnats andother little •

[130] CSG-PL-systems Using GAs to improve the visualquality of fractal plants generated with •

[99] curves Grammatical evol. to design fractal • with a

given dimension[41] Darwin Disney meets • – the evol. of funny animated

figures[58] delights In the infinity of computer space there is a gar-

den of unearthly •

[137] design A two-stage evol. model for the computer-aided• of colour combinations

[16] – Appl. of GA to aesthetic • of bridge structures[120] – Appl. of GA to • of artificial ground[31] – Appl. of interactive GA to fashion •

[36] – Automatic • support and image evaluation of two-coloured products using colour association and colour harmonyscales and GA

[56] – Computer sculpture • and animation



Permuted title index 21

[100] – Evol. • of objects using scene graphs[35] – FPGA realisation of the GA for the • of gray-scale soft

morphological filters[99] – Grammatical evol. to • fractal curves with a given di-

mension[21] – House • syst. using GA[119] – Interactive evol. alg. in •

[146] – Interactive GA-based • support syst. for lighting • in3-D computer graphics

[125] – Interactive GA-based • support syst. for lighting • incomputer graphics

[79] – Motion • of a 3D-CG avatar that uses humanoid ani-mation

[23] – Opt. • of outdoor lighting syst. by GAs[20] designing Data structure for syst. kitchen editing and

•

[15] determining Evolving attractive faces using morphingtechnology and a GA: A new appr. to • ideal facial aesthetics

[147] developmental Evol. and coevol. of • prog.[184] device Method and • for generating musical sound

waveform[111] diagram A cat’s cradle string • display method based

on a GA[108] diagrams Automating the layout of network • with

specified visual organization[141] – Placing text labels on maps and • using GAs with

masking[32] digital Evol. of • images[99] dimension Grammatical evol. to design fractal curves

with a given •

[72] Discrete summation synthesis of musical instrumenttones using GAs

[41] Disney meets Darwin – the evol. of funny animated fig-ures

[111] display A cat’s cradle string diagram • method basedon a GA

[70] douple Automated parameter opt. for • frequency mod-ulation synthesis using the gen. annealing alg.

[17] drawing A GA for • undirected graphs[121] – Automatic graph • by gen. search[143] – Gen. graph •

[142] – Opt. of flowsheet • layout using a GA[172] drum A • shape opt. by GAs[68] dynamic Wavetable matching synthesis of • instru-

ments with GAs[50] dynamical Interactive evol. of • syst.[162] ecosystems Evolving sonic •

[20] editing Data structure for syst. kitchen • and designing[29] efficacy GA search • in aesthetic product spaces[97] efficient An • evol. alg. for accurate polygonal approx-

imation[67] • model fitting using a GA: pole-zero approximations of

HRTFs[60] elaa Alkavatko taideteoksetkin • [Is art getting life?][163] electronic A novel appr. to automatic music transcrip-

tion using • synthesis and GAs[164] • synthesis using GAs for automatic music transcription[28] emergent Learning • style using an evol. appr.[117] Entwicklungsprogrammen MathEvolvica –

Simulierte Evol. von • der Natur[40] Envelope matching with GAs[174] environment GeNotator: An • for investigating the

appl. of GAs in computer assisted composition[110] Equation Approximation der Rendering • durch Evol.

are Alg. en[51, 52] equations Interactive evol. of • for procedural models[98] Estimating parameters for procedural texturing by

GAs[36] evaluation Automatic design support and image • of

two-coloured products using colour association and colour har-mony scales and GA

[179] – GA utilising neural network fitness • for musical com-position

[105] • of GA-generated multivariate color tables for the vi-sualization of multimodal medical fused data sets

[25] – Roof shape generation method for buildings usingKANSEI • rules

[180] evolution A hybrid neuro-gen. pattern • syst. appl. tomusical composition

[118] – An • model for integration problems[91] – Animating the • process of GAs

[49] – Artificial • for computer graphics[158, 160] – Automatic composition of music by means of gram-

matical •[169] – Bach in a box: The • of four part baroque harmony

using the GA[41] – Disney meets Darwin – the • of funny animated figures[117] – MathEvolvica – Simulierte • von Entwicklungsprog.

men der Natur[135] – Principia Evolvica, Simulierte • mit Mathematica[126] – Evolving • prog. : Gen. prog. and L-syst.[44] – FormSynth: The rule-based • of complex forms from

geometric primitives[89] – Gen. prog. • of cntr. for 3-D character animation[99] – Grammatical • to design fractal curves with a given

dimension[50] – Interactive • of dynamical syst.[51, 52] – Interactive • of equations for procedural models[54] – Mutator, a subjective human interface for • of com-

puter sculptures[147] • and coevol. of developmental prog.[32] • of digital images[134] • prog. evolved[22] – Preferred surface luminances in offices, by • a pilot

study[39] – Towards automated artificial • for computer-generated

images[42] Evolution strategies with subjective sel.[110] Evolutionare Approximation der Rendering Equation

durch • Alg. en[137] evolutionary A two-stage • model for the computer-

aided design of colour combinations[97] – An efficient • alg. for accurate polygonal approxima-

tion[81] – Automatic cntr. of physically realistic animated figures

using • prog.[84] – Building new tools for synthetic image animation by

using • techniques[96] – Illustrating • Computation with Mathematica[119] – Interactive • alg. in design[28] – Learning emergent style using an • appr.[165] • alg. and automatic transcription of music[80] • alg. in modeling and animation[57] • Art and Computers[148] • data visualization[100] • design of objects using scene graphs[86] • ident. of cloth animation models[114] • learning of graph layout constraints from examples[181] • methods for musical composition[93] – Patterns of cluster formation and • activity in evolving

L-syst.[109] – Rayvolution: an • ray tracing alg.[112] – Rayvolution: An • ray tracing alg.[115] – Simulation of Global Illumination: An • Appr.[47] – The appl. of • and biological processes to computer art

and animation[75] evolutionary strategies Training partially recurrent

neural networks using •

[59] evoluution Kaarmemaiset sykkyrat pyorivat, hajoavat ja kulkevat itsensa lapi, Tietokonetaiteilija William Lathamluo olioitaan • saantojen avulla [Refers to works of computerartist William Latham]

[134] evolved Evol. prog. •

[135] Evolvica Principia • Simulierte Evol. mit Mathemat-

ica

[124] evolving Gen. L-syst. prog. : breeding and • artificialflowers with Mathematica

[15] • attractive faces using morphing technology and a GA:

A new appr. to determining ideal facial aesthetics[126] • evol. prog. : Gen. prog. and L-syst.[132] • fractal movies[116] • fractals[53] • images[161] • intelligent musical materials[38] • line drawings[162] • sonic ecosyst.[113] • virtual creatures[93] – Patterns of cluster formation and evol. activity in •

L-syst.[178] ex Musica • machina: composing 16th-century counter-

point with gen. prog. and symbiosis[66] Experiances of otoneurological expert syst. for vertigo




[106] experience Modelling video games’ landscapes bymeans of gen. terrain prog. - A new appr. for improvingusers’ •

[66] expert Experiances of otoneurological • syst. for ver-tigo

[90] explain The use of animation to • GAs[83] expression Searching for facial • by GA[95] eye Is beauty in the • of the beholder[15] faces Evolving attractive • using morphing technology

and a GA: A new appr. to determining ideal facial aesthetics[15] facial Evolving attractive faces using morphing technol-

ogy and a GA: A new appr. to determining ideal • aesthetics[83] – Searching for • expression by GA[31] fashion Appl. of interactive GA to • design[76] feedback Nested modulator and • FM matching of in-

strument tones[62] fetishes Self-evolving arts— Organisms versus •

[82] figure Gen. prog. for articulated • motion[81] figures Automatic cntr. of physically realistic animated

• using EP[41] – Disney meets Darwin – the evol. of funny animated •

[77] – Global Opt. for Articulated • Molecular Structure Pre-diction and Motion Synthesis for Animation

[34] film GA opt. of multidimensional grayscale soft morpho-logical filters with appl. in • archive restoration

[35] filters FPGA realisation of the GA for the design of gray-scale soft morphological •

[34] – GA opt. of multidimensional grayscale soft morpholog-ical • with appl. in film archive restoration

[139] fish Where to • for neural nets[179] fitness GA utilising neural network • evaluation for mu-

sical composition[175] fitness functions Neural network • for a musical IGA[67] fitting Efficient model • using a GA: pole-zero approxi-

mations of HRTFs[67] – Hearing Aid • with GAs[124] flowers Gen. L-syst. prog. : breeding and evolving

artificial • with Mathematica[142] flowsheet Opt. of • drawing layout using a GA[156] FM Machine tongues XVI. GAs and their appl. to •

matching synthesis[76] – Nested modulator and feedback • matching of instru-

ment tones[93] formation Patterns of cluster • and evol. activity in

evolving L-syst.[44] forms FormSynth: The rule-based evol. of complex •

from geometric primitives[44] FormSynth The rule-based evol. of complex forms

from geometric primitives[35] FPGA realisation of the GA for the design of gray-scale

soft morphological filters[132] fractal Evolving • movies[99] – Grammatical evol. to design • curves with a given di-

mension[130] – Using GAs to improve the visual quality of • plants

generated with CSG-PL-syst.[131] fractal image An improved GA of solving IFS code of

•

[116] fractals Evolving •

[70] frequency Automated parameter opt. for douple •

modulation synthesis using the gen. annealing alg.[69] – Automatic parameter opt. for double • modulation

synthesis using the gen. annealing alg.[78] functional Using physically-based models and GAs for

• composition of sound signals, synchronized to animated mo-tion

[41] funny Disney meets Darwin – the evol. of • animatedfigures

[105] fused Evaluation of GA-generated multivariate color ta-bles for the visualization of multimodal medical • data sets

[30] Future Geneesys – katsaus kolmiulotteiseen kei-noelamaan nyt ja hahmotelma tulevaisuudesta [A Review of 3D AL and Outline of its •

[122] fuzzy A • cntr. rendering syst. for virtual reality syst.optimised by GAs

[87] GA-based An automatic • construction of neural net-works for motion cntr. of virtual life

[146] – Interactive • design support syst. for lighting design in3-D computer graphics

[125] – Interactive • design support syst. for lighting design incomputer graphics

[65] • noisy speech recognition using two-dimensional cep-strum

[58] garden In the infinity of computer space there is a • of unearthly delights

[1] GArphics - Applying GAs for generating graphics[30] Geneesys – katsaus kolmiulotteiseen keinoelamaan nyt

ja hahmotelma tulevaisuudesta [A Review of 3D AL and Out-line of its Future]

[130] generated Using GAs to improve the visual quality of fractal plants • with CSG-PL-syst.

[1] generating GArphics - Applying GAs for • graphics[167] – GenJam: A GA for • jazz solos[184] – Method and device for • musical sound waveform[166] • rhytms with GAs[182] generation A GA for the • of jazz melodies[173] – A grammar based gen. prog. technique appl. to music

•

[168] – GAs in musical style oriented •

[123] – Gen. prog. for easy 3D texture •

[25] – Roof shape • method for buildings using KANSEI eval-uation rules

[26] Generic building product model incorporating buildingtype info

[167] GenJam A GA for generating jazz solos[177] GenJam An interactive GA jazz improviser[174] GeNotator An environment for investigating the appl.

of GAs in computer assisted composition[44] geometric primitives FormSynth: The rule-based

evol. of complex forms from •

[60] getting Alkavatko taideteoksetkin elaa? [Is art • life?][136] global A neuro-evol. unbiased • illumination alg.[77] • Opt. for Articulated Figures: Molecular Structure

Prediction and Motion Synthesis for Animation[115] – Simulation of • Illumination: An Evol. Appr.[85] Gnats Keinoelamaa virtuaalitodellisuudessa – hyttysia

ja muita otokoita [Artificial life in virtual reality – • and otherlittle creatures]

[173] grammar A • based gen. prog. technique appl. tomusic generation

[158, 160] grammatical Automatic composition of music bymeans of • evol.

[99] • evol. to design fractal curves with a given dimension[121] graph Automatic • drawing by gen. search[114] – Evol. learning of • layout constraints from examples[143] – Gen. • drawing[94] Graphic object layout with interactive GAs[49] graphics Artificial evol. for computer •[1] – GArphics - Applying GAs for generating •

[125] – Interactive GA-based design support syst. for lightingdesign in computer •

[17] graphs A GA for drawing undirected •

[35] gray-scale FPGA realisation of the GA for the designof • soft morphological filters

[34] grayscale GA opt. of multidimensional • soft morpho-logical filters with appl. in film archive restoration

[120] ground Appl. of GA to design of artificial •[71] Group synthesis with GAs[145] growth Lifelike artificial trees based on • iterated func-

tion syst.[30] hahmotelma Geneesys – katsaus kolmiulotteiseen kei-

noelamaan nyt ja • tulevaisuudesta [A Review of 3D AL andOutline of its Future]

[59] hajoavat Kaarmemaiset sykkyrat pyorivat, • ja kulke-vat itsensa lapi, Tietokonetaiteilija William Latham luoolioitaan evoluution saantojen avulla [Refers to works of com-puter artist William Latham]

[170] Harmonisation of musical progression with GAs

[169] harmony Bach in a box: The evol. of four part baroque• using the GA

[67] Hearing Aid Fitting with GAs[21] House design syst. using GA[18, 19 ] House design syst. using GA[67] HRTFs Efficient model fitting using a GA: pole-zero ap-

proximations of •[54] human Mutator, a subjective • interface for evol. of

computer sculptures[79] humanoid Motion design of a 3D-CG avatar that uses

• animation[180] hybrid A • neuro-gen. pattern evol. syst. appl. to

musical composition[74] • sampling-wavetable synthesis with GAs




[85] hyttysia Keinoelamaa virtuaalitodellisuudessa – • jamuita otokoita [Artificial life in virtual reality – Gnats andother little creatures]

[15] ideal Evolving attractive faces using morphing technol-ogy and a GA: A new appr. to determining • facial aesthetics

[86] identification Evol. • of cloth animation models[131] IFS code An improved GA of solving • of fractal image[175] IGA Neural network fitness functions for a musical •[136] illumination A neuro-evol. unbiased global • alg.[115] – Simulation of Global • An Evol. Appr.[96] Illustrating Evol. Computation with Mathematica[61] ilmioiden Tietokonetaide on monien • leikkauspiste

[Computer art][36] image Automatic design support and • evaluation of


[84] – Building new tools for synthetic • animation by usingevol. techniques

[140] – Recovery of superquadric primitives from a range • us-ing GA

[32] images Evol. of digital •[53] – Evolving •

[24] – Lighting quality research using rendered • of offices[128] – Shape modeling of multiple objects from shading • us-

ing GAs[133] – Superquadrics modeling of multiple objects from shad-

ing • using GAs[39] – Towards automated artificial evol. for computer-

generated •

[177] improviser GenJam: An interactive GA jazz •

[58] infinity In the • of computer space there is a garden of unearthly delights

[26] information Generic building product model incorpo-rating building type •

[63] instrument Methods for multiple wavetable synthesisof musical • tones

[76] – Nested modulator and feedback FM matching of •tones

[68] instruments Wavetable matching synthesis of dynamic• with GAs

[118] integration An evol. model for • problems[161] intelligent Evolving • musical materials[138] interactive 3-D CG lighting with an • GA[31] – Appl. of • GA to fashion design[177] – GenJam: An • GA jazz improviser[94] – Graphic object layout with • GAs[50] • evol. of dynamical syst.[51, 52] • evol. of equations for procedural models[119] • evol. alg. in design[146] • GA-based design support syst. for lighting design in

3-D computer graphics[125] • GA-based design support syst. for lighting design in

computer graphics[33] interactive)art AI in contemporary •

[54] interface Mutator, a subjective human • for evol. of computer sculptures

[73] interpolation Computation and memory tradeoffs withmultiple wavetable •

[174] investigating GeNotator: An environment for • theappl. of GAs in computer assisted composition

[145] iterated function system Lifelike artificial treesbased on growth •

[59] itsensa Kaarmemaiset sykkyrat pyorivat, hajoavat jakulkevat • lapi, Tietokonetaiteilija William Latham luoolioitaan evoluution saantojen avulla [Refers to works of com-puter artist William Latham]

[182] jazz A GA for the generation of • melodies[167] – GenJam: A GA for generating • solos[177] – GenJam: An interactive GA • improviser[25] KANSEI Roof shape generation method for buildings

using • evaluation rules[30] katsaus Geneesys – • kolmiulotteiseen keinoelamaan

nyt ja hahmotelma tulevaisuudesta [A Review of 3D AL andOutline of its Future]

[85] Keinoelamaa virtuaalitodellisuudessa – hyttysia jamuita otokoita [Artificial life in virtual reality – Gnats andother little creatures]

[30] keinoelamaan Geneesys – katsaus kolmiulotteiseen •

nyt ja hahmotelma tulevaisuudesta [A Review of 3D AL andOutline of its Future]

[20] kitchen Data structure for syst. • editing and designing

[30] kolmiulotteiseen Geneesys – katsaus • keinoelamaannyt ja hahmotelma tulevaisuudesta [A Review of 3D AL andOutline of its Future]

[59] kulkevat Kaarmemaiset sykkyrat pyorivat, hajoavat ja • itsensa lapi, Tietokonetaiteilija William Latham luoolioitaan evoluution saantojen avulla [Refers to works of com-puter artist William Latham]

[141] labels Placing text • on maps and diagrams using GAswith masking

[106] landscapes Modelling video games’ • by means of gen.terrain prog. - A new appr. for improving users’ experience

[59] Latham Kaarmemaiset sykkyrat pyorivat, hajoavat jakulkevat itsensa lapi, Tietokonetaiteilija William Latham luoolioitaan evoluution saantojen avulla [Refers to works of com-puter artist William •

[59] – Kaarmemaiset sykkyrat pyorivat, hajoavat ja kulke-vat itsensa lapi, Tietokonetaiteilija William • luo olioitaanevoluution saantojen avulla [Refers to works of computer artistWilliam Latham]

[108] layout Automating the • of network diagrams with spec-ified visual organization

[114] – Evol. learning of graph • constraints from examples[94] – Graphic object • with interactive GAs[142] – Opt. of flowsheet drawing • using a GA[114] learning Evol. • of graph layout constraints from ex-

amples[28] • emergent style using an evol. appr.[61] leikkauspiste Tietokonetaide on monien ilmioiden •

[Computer art][27] levels Artificial intelligence appr. to the prediction of

nat. lighting •

[60] life Alkavatko taideteoksetkin elaa? [Is art getting •

[87] – An automatic GA-based construction of neural net-works for motion cntr. of virtual •

[30] – Geneesys – katsaus kolmiulotteiseen keinoelamaan nyt ja hahmotelma tulevaisuudesta [A Review of 3D Artificial •

and Outline of its Future][145] Lifelike artificial trees based on growth iterated func-

tion syst.[138] lighting 3-D CG • with an interactive GA[27] – Artificial intelligence appr. to the prediction of nat. •

levels[146] – Interactive GA-based design support syst. for • design

in 3-D computer graphics[125] – Interactive GA-based design support syst. for • design

in computer graphics[24] • quality research using rendered images of offices[23] – Opt. design of outdoor • syst. by GAs[144] Lindenmayer On GAs and • syst.[38] line drawings Evolving •

[124] L-system Gen. • prog. : breeding and evolving artifi-cial flowers with Mathematica

[107] – Gen. • prog.[149] L-system Morphogenesis of path plan sequences

through gen. synthesis of • productions[126] L-systems Evolving evol. prog. : Gen. prog. and •

[93] – Patterns of cluster formation and evol. activity inevolving •

[22] luminances Preferred surface • in offices, by evol. : apilot study

[59] luo Kaarmemaiset sykkyrat pyorivat, hajoavat ja kulke-vat itsensa lapi, Tietokonetaiteilija William Latham •

olioitaan evoluution saantojen avulla [Refers to works of com-puter artist William Latham]

[178] machina Musica ex • composing 16th-century counter-point with gen. prog. and symbiosis

[156] Machine tongues XVI. GAs and their appl. to FM

matching synthesis[141] maps Placing text labels on • and diagrams using GAs

with masking[141] masking Placing text labels on maps and diagrams us-

ing GAs with •

[156] matching Machine tongues XVI. GAs and their appl.to FM • synthesis

[76] – Nested modulator and feedback FM • of instrumenttones

[68] – Wavetable • synthesis of dynamic instruments withGAs

[161] materials Evolving intelligent musical •[135] Mathematica Principia Evolvica, Simulierte Evol.

mit •




[124] Mathematica Gen. L-syst. prog. : breeding andevolving artificial flowers with •

[96] Mathematica Illustrating Evol. Computation with •

[117] MathEvolvica – Simulierte Evol. von Entwick-lungsprog. men der Natur

[105] medical Evaluation of GA-generated multivariate colortables for the visualization of multimodal • fused data sets

[41] meets Disney • Darwin – the evol. of funny animatedfigures

[182] melodies A GA for the generation of jazz •

[73] memory Computation and • tradeoffs with multiplewavetable interpolation

[137] model A two-stage evol. • for the computer-aided de-sign of colour combinations

[118] – An evol. • for integration problems[67] – Efficient • fitting using a GA: pole-zero approximations

of HRTFs[80] modeling Evol. alg. in • and animation[171] – Sel. of attributed for • Bach chorales by a GA[128] – Shape • of multiple objects from shading images using

GAs[133] – Superquadrics • of multiple objects from shading im-

ages using GAs[106] Modelling video games’ landscapes by means of gen.

terrain prog. - A new appr. for improving users’ experience[88] – Three-dimensional colour image and animation • for

CAL[101] models Building photorealistic • using data fusion[102] – Creating photorealistic • by data fusion with GAs[86] – Evol. ident. of cloth animation •

[51, 52] – Interactive evol. of equations for procedural •[104] – Photorealistic 3D • of Real-World Objects[78] – Using physically-based • and GAs for functional com-

position of sound signals, synchronized to animated motion[70] modulation Automated parameter opt. for douple fre-

quency • synthesis using the gen. annealing alg.[69] – Automatic parameter opt. for double frequency • syn-

thesis using the gen. annealing alg.[76] modulator Nested • and feedback FM matching of in-

strument tones[77] Molecular Global Opt. for Articulated Figures: •

Structure Prediction and Motion Synthesis for Animation[61] monien Tietokonetaide on • ilmioiden leikkauspiste

[Computer art][15] morphing Evolving attractive faces using • technology

and a GA: A new appr. to determining ideal facial aesthetics[149] Morphogenesis of path plan sequences through gen.

synthesis of L-syst. productions[35] morphological FPGA realisation of the GA for the de-

sign of gray-scale soft • filters[34] – GA opt. of multidimensional grayscale soft • filters

with appl. in film archive restoration[87] motion An automatic GA-based construction of neural

networks for • cntr. of virtual life[82] – Gen. prog. for articulated figure •

[77] – Global Opt. for Articulated Figures: Molecular Struc-ture Prediction and • Synthesis for Animation

[92] • blending using a CS[79] • design of a 3D-CG avatar that uses humanoid anima-

tion[78] – Using physically-based models and GAs for functional

composition of sound signals, synchronized to animated •

[132] movies Evolving fractal •[85] muita Keinoelamaa virtuaalitodellisuudessa – hyttysia

ja • otokoita [Artificial life in virtual reality – Gnats and otherlittle creatures]

[34] multidimensional GA opt. of • grayscale soft mor-phological filters with appl. in film archive restoration

[105] multimodal Evaluation of GA-generated multivariatecolor tables for the visualization of • medical fused data sets

[105] multivariate Evaluation of GA-generated • color tablesfor the visualization of multimodal medical fused data sets

[173] music A grammar based gen. prog. technique appl. to• generation

[163] – A novel appr. to automatic • transcription using elec-tronic synthesis and GAs

[158, 160] – Automatic composition of • by means of grammat-ical evol.

[164] – Electronic synthesis using GAs for automatic • tran-scription

[165] – Evol. alg. and automatic transcription of •

[155] – GA composes •

[152, 153, 154] – GAs and computer-assisted • composition[185] – Gen. • compositor[43] – Indexed Bibliography of GAs in Art and •

[159] • recognition syst. using ART-1 and GA[157] – Neurogen, • composition using GAs and cooperating

neural networks[178] Musica ex machina: composing 16th-century counter-

point with gen. prog. and symbiosis[180] musical A hybrid neuro-gen. pattern evol. syst. appl.

to • composition[181] – Evol. methods for • composition[161] – Evolving intelligent • materials[179] – GA utilising neural network fitness evaluation for •

composition[170] – Harmonisation of • progression with GAs[184] – Method and device for generating • sound waveform[63] – Methods for multiple wavetable synthesis of • instru-

ment tones[175] – Neural network fitness functions for a • IGA[72] musical instrument Discrete summation synthesis of

• tones using GAs[168] musical style GAs in • oriented generation[54] Mutator a subjective human interface for evol. of com-

puter sculptures[117] Natur MathEvolvica – Simulierte Evol. von Entwick-

lungsprog. men der •

[27] natural Artificial intelligence appr. to the prediction of • lighting levels

[76] Nested modulator and feedback FM matching of instru-ment tones

[108] network Automating the layout of • diagrams withspecified visual organization

[139] neural nets Where to fish for •

[179] neural network GA utilising • fitness evaluation formusical composition

[175] • fitness functions for a musical IGA[87] neural networks An automatic GA-based construc-

tion of • for motion cntr. of virtual life[157] – Neurogen, music composition using GAs and cooper-

ating •

[75] – Training partially recurrent • using evol. strategies[136] neuro-evolutionary A • unbiased global illumination

alg.[157] Neurogen music composition using GAs and cooperat-

ing neural networks[180] neuro-genetic A hybrid • pattern evol. syst. appl. to

musical composition[65] noisy GA-based • speech recognition using two-

dimensional cepstrum[30] nyt Geneesys – katsaus kolmiulotteiseen keinoelamaan •

ja hahmotelma tulevaisuudesta [A Review of 3D AL and Out-line of its Future]

[94] object Graphic • layout with interactive GAs[100] objects Evol. design of • using scene graphs[104] – Photorealistic 3D Models of Real-World •

[128] – Shape modeling of multiple • from shading images us-ing GAs

[133] – Superquadrics modeling of multiple • from shading im-ages using GAs

[24] offices Lighting quality research using rendered imagesof •

[22] – Preferred surface luminances in • by evol. : a pilotstudy

[59] olioitaan Kaarmemaiset sykkyrat pyorivat, hajoavat jakulkevat itsensa lapi, Tietokonetaiteilija William Latham luo• evoluution saantojen avulla [Refers to works of computer

artist William Latham][23] Optimal design of outdoor lighting syst. by GAs[122] optimised A fuzzy cntr. rendering syst. for virtual re-

ality syst. • by GAs[151] Optimized connection of rational surface-based on GAs[183] Optimizing additive synthesis parameters with GAs

and self-organizing maps[129] Organic art[62] Organisms Self-evolving arts— • versus fetishes[108] organization Automating the layout of network dia-

grams with specified visual •

[168] oriented GAs in musical style • generation[66] otoneurological Experiances of • expert syst. for ver-

tigo




[23] outdoor Opt. design of • lighting syst. by GAs[48] Panspermia[70] parameter Automated • opt. for douple frequency

modulation synthesis using the gen. annealing alg.[69] – Automatic • opt. for double frequency modulation syn-

thesis using the gen. annealing alg.[98] parameters Estimating • for procedural texturing by

GAs[183] – Opt. additive synthesis • with GAs and self-organizing

maps[75] partially Training • recurrent neural networks using

evol. strategies[149] path Morphogenesis of • plan sequences through gen.

synthesis of L-syst. productions[180] pattern A hybrid neuro-gen. • evol. syst. appl. to

musical composition[93] Patterns of cluster formation and evol. activity in

evolving L-syst.[64] peak Low • amplitudes for wavetable synthesis[103] perceptual An appr. to the • opt. of complex visual-

izations[101] photorealistic Building • models using data fusion[102] – Creating • models by data fusion with GAs[104] • 3D Models of Real-World Objects[81] physically Automatic cntr. of • realistic animated fig-

ures using EP[78] physically-based Using • models and GAs for func-

tional composition of sound signals, synchronized to animatedmotion

[22] pilot Preferred surface luminances in offices, by evol. :a • study

[141] Placing text labels on maps and diagrams using GAswith masking

[149] plan Morphogenesis of path • sequences through gen.synthesis of L-syst. productions

[130] plants Using GAs to improve the visual quality of frac-tal • generated with CSG-PL-syst.

[67] pole-zero Efficient model fitting using a GA: • approx-imations of HRTFs

[97] polygonal approximation An efficient evol. alg. foraccurate •

[27] prediction Artificial intelligence appr. to the • of nat.lighting levels

[77] – Global Opt. for Articulated Figures: Molecular Struc-ture • and Motion Synthesis for Animation

[22] Preferred surface luminances in offices, by evol. : apilot study

[140] primitives Recovery of superquadric • from a range im-age using GA

[135] Principia Evolvica, Simulierte Evol. mit Mathematica

[98] procedural Estimating parameters for • texturing byGAs

[51, 52] – Interactive evol. of equations for • models[91] process Animating the evol. • of GAs[47] processes The appl. of evol. and biological • to com-

puter art and animation[37] product Automatic • color design using gen. searching[29] – GA search efficacy in aesthetic • spaces[26] product model Generic building • incorporating

building type info[149] productions Morphogenesis of path plan sequences

through gen. synthesis of L-syst. •[36] products Automatic design support and image evalu-

ation of two-coloured • using colour association and colourharmony scales and GA

[81] programming Automatic cntr. of physically realisticanimated figures using evol. •

[124] – Gen. L-syst. • breeding and evolving artificial flowerswith Mathematica

[107] – Gen. L-syst. •

[106] – Modelling video games’ landscapes by means of gen.terrain • - A new appr. for improving users’ experience

[170] progression Harmonisation of musical • with GAs[59] pyorivat Kaarmemaiset sykkyrat • hajoavat ja kulkevat

itsensa lapi, Tietokonetaiteilija William Latham luo olioitaanevoluution saantojen avulla [Refers to works of computer artistWilliam Latham]

[24] quality Lighting • research using rendered images of of-fices

[130] – Using GAs to improve the visual • of fractal plantsgenerated with CSG-PL-syst.

[140] range Recovery of superquadric primitives from a • im-age using GA

[151] rational Optimized connection of • surface-based onGAs

[109] ray tracing Rayvolution: an evol. • alg.[112] – Rayvolution: An evol. • alg.[109] Rayvolution an evol. ray tracing alg.[112] • An evol. ray tracing alg.[35] realisation FPGA • of the GA for the design of gray-

scale soft morphological filters[81] realistic Automatic cntr. of physically • animated fig-

ures using EP[85] reality Keinoelamaa virtuaalitodellisuudessa – hyttysia

ja muita otokoita [Artificial life in virtual • – Gnats and otherlittle creatures]

[104] Real-World Photorealistic 3D Models of • Objects[65] recognition GA-based noisy speech • using two-

dimensional cepstrum[159] – Music • syst. using ART-1 and GA[140] Recovery of superquadric primitives from a range im-

age using GA[75] recurrent Training partially • neural networks using

evol. strategies[59] Refers Kaarmemaiset sykkyrat pyorivat, hajoavat ja

kulkevat itsensa lapi, Tietokonetaiteilija William Latham luoolioitaan evoluution saantojen avulla • to works of computerartist William Latham]

[24] rendered Lighting quality research using • images of offices

[122] rendering A fuzzy cntr. • syst. for virtual reality syst.optimised by GAs

[110] – Approximation der • Equation durch Evol. are Alg. en[24] research Lighting quality • using rendered images of of-

fices[34] restoration GA opt. of multidimensional grayscale soft

morphological filters with appl. in film archive •

[30] Review Geneesys – katsaus kolmiulotteiseen kei-noelamaan nyt ja hahmotelma tulevaisuudesta [A • of 3D ALand Outline of its Future]

[166] rhytms Generating • with GAs[25] Roof shape generation method for buildings using KAN-

SEI evaluation rules[44] rule-based FormSynth: The • evol. of complex forms

from geometric primitives[25] rules Roof shape generation method for buildings using

KANSEI evaluation •

[74] sampling-wavetable Hybrid • synthesis with GAs[36] scales Automatic design support and image evaluation

of two-coloured products using colour association and colourharmony • and GA

[100] scene graphs Evol. design of objects using •

[56] sculpture Computer • design and animation[54] sculptures Mutator, a subjective human interface for

evol. of computer •

[45, 46] • in the void[121] search Automatic graph drawing by gen. •[29] – GA • efficacy in aesthetic product spaces[37] searching Automatic product color design using gen. •[83] • for facial expression by GA[42] selection Evol. strategies with subjective •

[171] • of attributed for modeling Bach chorales by a GA[62] Self-evolving arts— Organisms versus fetishes[183] self-organizing maps Opt. additive synthesis param-

eters with GAs and •

[149] sequences Morphogenesis of path plan • through gen.synthesis of L-syst. productions

[105] sets Evaluation of GA-generated multivariate color ta-bles for the visualization of multimodal medical fused data •

[128] shading Shape modeling of multiple objects from • im-ages using GAs

[133] – Superquadrics modeling of multiple objects from • im-ages using GAs

[172] shape A drum • opt. by GAs[128] • modeling of multiple objects from shading images us-

ing GAs[127] • transformation in space-time[25] – Roof • generation method for buildings using KANSEI

evaluation rules[78] signals Using physically-based models and GAs for

functional composition of sound • synchronized to animatedmotion




[115] Simulation of Global Illumination: An Evol. Appr.[117] Simulierte MathEvolvica – • Evol. von Entwick-

lungsprog. men der Natur[135] – Principia Evolvica, • Evol. mit Mathematica[35] soft FPGA realisation of the GA for the design of gray-

scale • morphological filters[34] – GA opt. of multidimensional grayscale • morphological

filters with appl. in film archive restoration[167] solos GenJam: A GA for generating jazz •

[162] sonic Evolving • ecosyst.[184] sound Method and device for generating musical • wave-

form[78] – Using physically-based models and GAs for functional

composition of • signals, synchronized to animated motion[58] space In the infinity of computer • there is a garden of

unearthly delights[29] spaces GA search efficacy in aesthetic product •

[127] space-time Shape transformation in •

[108] specified Automating the layout of network diagramswith • visual organization

[65] speech GA-based noisy • recognition using two-dimensional cepstrum

[111] string A cat’s cradle • diagram display method basedon a GA

[20] structure Data • for syst. kitchen editing and design-ing

[77] – Global Opt. for Articulated Figures: Molecular • Pre-diction and Motion Synthesis for Animation

[16] structures Appl. of GA to aesthetic design of bridge •

[28] style Learning emergent • using an evol. appr.[42] subjective Evol. strategies with • sel.[54] – Mutator, a • human interface for evol. of computer

sculptures[72] summation Discrete • synthesis of musical instrument

tones using GAs[140] superquadric Recovery of • primitives from a range

image using GA[133] Superquadrics modeling of multiple objects from

shading images using GAs[36] support Automatic design • and image evaluation of


[146] – Interactive GA-based design • syst. for lighting designin 3-D computer graphics

[125] – Interactive GA-based design • syst. for lighting designin computer graphics

[22] surface Preferred • luminances in offices, by evol. : apilot study

[151] surface-based Optimized connection of rational • onGAs

[55] surreal Artificial life or • art?[59] sykkyrat Kaarmemaiset • pyorivat, hajoavat ja kulke-

vat itsensa lapi, Tietokonetaiteilija William Latham luoolioitaan evoluution saantojen avulla [Refers to works of com-puter artist William Latham]

[178] symbiosis Musica ex machina: composing 16th-centurycounterpoint with gen. prog. and •

[78] synchronized Using physically-based models and GAsfor functional composition of sound signals, • to animated mo-tion

[163] synthesis A novel appr. to automatic music transcrip-tion using electronic • and GAs

[70] – Automated parameter opt. for douple frequency mod-ulation • using the gen. annealing alg.

[69] – Automatic parameter opt. for double frequency mod-ulation • using the gen. annealing alg.

[72] – Discrete summation • of musical instrument tones us-

ing GAs[164] – Electronic • using GAs for automatic music transcrip-

tion[77] – Global Opt. for Articulated Figures: Molecular Struc-

ture Prediction and Motion • for Animation[71] – Group • with GAs[74] – Hybrid sampling-wavetable • with GAs[64] – Low peak amplitudes for wavetable •

[156] – Machine tongues XVI. GAs and their appl. to FMmatching •

[63] – Methods for multiple wavetable • of musical instrumenttones

[149] – Morphogenesis of path plan sequences through gen. •

of L-syst. productions

[183] – Opt. additive • parameters with GAs and self-organizing maps

[68] – Wavetable matching • of dynamic instruments withGAs

[84] synthetic Building new tools for • image animation byusing evol. techniques

[60] taideteoksetkin Alkavatko • elaa? [Is art getting life?][84] techniques Building new tools for synthetic image an-

imation by using evol. •

[15] technology Evolving attractive faces using morphing •

and a GA: A new appr. to determining ideal facial aesthetics[106] terrain Modelling video games’ landscapes by means of

gen. • prog. - A new appr. for improving users’ experience[141] text Placing • labels on maps and diagrams using GAs

with masking[123] texture Gen. prog. for easy 3D • generation[98] texturing Estimating parameters for procedural • by

GAs[88] Three-dimensional colour image and animation mod-

elling for CAL[61] Tietokonetaide on monien ilmioiden leikkauspiste

[Computer art][59] Tietokonetaiteilija Kaarmemaiset sykkyrat pyorivat,

hajoavat ja kulkevat itsensa lapi, • William Latham luoolioitaan evoluution saantojen avulla [Refers to works of com-puter artist William Latham]

[176] tone Common • adaptive tuning using GAs[72] tones Discrete summation synthesis of musical instru-

ment • using GAs[63] – Methods for multiple wavetable synthesis of musical in-

strument •

[76] – Nested modulator and feedback FM matching of instru-ment •

[156] tongues Machine • XVI. GAs and their appl. to FMmatching synthesis

[84] tools Building new • for synthetic image animation byusing evol. techniques

[73] tradeoffs Computation and memory • with multiplewavetable interpolation

[75] Training partially recurrent neural networks using evol.strategies

[163] transcription A novel appr. to automatic music • us-ing electronic synthesis and GAs

[164] – Electronic synthesis using GAs for automatic music •

[165] – Evol. alg. and automatic • of music[127] transformation Shape • in space-time

[145] trees Lifelike artificial •

based on growth iterated func-tion syst.[30] tulevaisuudesta Geneesys – katsaus kolmiulotteiseen

keinoelamaan nyt ja hahmotelma • [A Review of 3D AL andOutline of its Future]

[176] tuning Common tone adaptive • using GAs[36] two-coloured Automatic design support and image

evaluation of • products using colour association and colourharmony scales and GA

[65] two-dimensional GA-based noisy speech recognitionusing • cepstrum

[137] two-stage A • evol. model for the computer-aided de-sign of colour combinations

[26] type Generic building product model incorporatingbuilding • info

[136] unbiased A neuro-evol. • global illumination alg.[17] undirected A GA for drawing • graphs[58] unearthly In the infinity of computer space there is a

garden of • delights

[106] users Modelling video games’ landscapes by means of gen. terrain prog. - A new appr. for improving • experience

[179] utilising GA • neural network fitness evaluation for mu-sical composition

[66] vertigo Experiances of otoneurological expert syst. for•

[106] video games Modelling • landscapes by means of gen.terrain prog. - A new appr. for improving users’ experience

[85] virtuaalitodellisuudessa Keinoelamaa • – hyttysia ja muita otokoita [Artificial life in virtual reality – Gnats andother little creatures]

[87] virtual An automatic GA-based construction of neuralnetworks for motion cntr. of • life

[113] – Evolving • creatures



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Notations

†(ref) = the bibliography item does not belong to my collection of genetic papers.(ref) = citation source code. ACM = ACM Guide to Computing Literature, EEA = Electrical & Elec-tronics Abstracts, BA = Biological Abstracts, CCA = Computers & Control Abstracts, CTI = CurrentTechnology Index, EI = The Engineering Index (A = Annual, M = Monthly), DAI = Dissertation Ab-stracts International, P = Index to Scientific & Technical Proceedings, PA = Physics Abstracts, PubMed= National Library of Medicine, BackBib = Thomas Back’s unpublished bibliography, Fogel/Bib = DavidFogel’s EA bibliography, etc* = only abstract seen.? = data of this field is missing (BiBTeX-format).

The last field in each reference item in Teletype font is the BiBTEXkey of the corresponding reference.

ftp://ftp.uwasa.fics/3NWGA/Bounsaythip.ps.Z

ftp://ftp.uwasa.fics/3NWGA/Kemenade.ps.Z

ftp://ftp.uwasa.fics/3NWGA/Kemenade.ps.Z

ftp://ftp.uwasa.fics/3NWGA/Bounsaythip.ps.Z



Appendix A

Abbreviations

The following other abbreviations were used to compress the titles of articles in the permutation titleindex:

AI = Artificial Intelligence

Alg. = Algorithm(s)AL = Artificial LifeANN(s) = Artificial Neural Net(work)(s)Appl. = Application(s), AppliedAppr. = Approach(es)Cntr. = Control, Controlled,

= Controlling, Controller(s)Coll. = ColloquiumComb. = CombinatorialConf. = ConferenceCS(s) = Classifier System(s)Distr. = DistributedEng. = EngineeringEP = Evolutionary Programming

ES = Evolutionsstrategie(n),= Evolution(ary) strategies

Evol. = Evolution, EvolutionaryExS(s) = Expert System(s)FF(s) = Fitness Function(s)GA(s) = Genetic Algorithm(s)Gen. = Genetic(s), Genetical(ly)GP = Genetic ProgrammingIdent. = IdentificationImpl. = Implementation(s)

Int. = International

ImPr = Image ProcessingJSS = Job Shop SchedulingML = Machine LearningNat. = NaturalNN(s) = Neural Net(work)(s)Opt. = Optimization, Optimal,

= Optimizer(s), OptimierungOR = Operation(s) ResearchPar. = Parallel, ParallelismPerf. = PerformancePop. = Population(s), Populational(ly)Proc. = ProceedingsProg. = Programming, Program(s), ProgrammedProb. = Problem(s)

QAP = Quadratic Assignment ProblemRep. = Representation(s), Representational(ly)SA = Simulated AnnealingSch. = Scheduling, Schedule(s)Sel. = Selection, SelectionismSymp. = SymposiumSyst. = System(s)Tech. = Technical, TechnologyTSP = Travel(l)ing Salesman Problem

41



Appendix B

Bibliography entry formats

This documentation was prepared with LATEX and reproduced from camera-ready copy supplied by the editor. The oneswho are familiar with BibTeX may have noticed that the references are printed using abbrv bibliography style and haveno difficulties in interpreting the entries. For those not so familiar with BibTeX are given the following formats of themost common entry types. The optional fields are enclosed by ”[ ]” in the format description. Unknown fields are shownby ”?”. † after the entry means that neither the article nor the abstract of the article was available for reviewing and sothe reference entry and/or its indexing may be more or less incomplete.

Book: Author(s), Title , Publisher, Publisher’s address, year.

Example

John H. Holland. Adaptation in Natural and Artificial Systems . The University of Michigan Press,Ann Arbor, 1975.

Journal article: Author(s), Title, Journal , volume(number): first page – last page, [month,] year.

Example

David E. Goldberg. Computer-aided gas pipeline operation using genetic algorithms and rule learning.Part I: Genetic algorithms in pipeline optimization. Engineering with Computers , 3(?):35–45, 1987.† .

Note: the number of the journal unknown, the article has not been seen.Proceedings article: Author(s), Title, editor(s) of the proceedings, Title of Proceedings, [volume,] pages, location of theconference, date of the conference, publisher of the proceedings, publisher’s address.

ExampleJohn R. Koza. Hierarchical genetic algorithms operating on populations of computer programs. InN. S. Sridharan, editor, Eleventh International Joint Conference on Artificial Intelligence (IJCAI-89),pages 768–774, Detroit, MI, 20.-25. August 1989. Morgan Kaufmann, Palo Alto, CA. † .

Technical report: Author(s), Title, type and number, institute, year.

Example

Thomas Back, Frank Hoffmeister, and Hans-Paul Schwefel. Applications of evolutionary algorithms.Technical Report SYS-2/92, University of Dortmund, Department of Computer Science, 1992.

42



Vaasa GA Bibliography 43

Vaasa Genetic Algorithm Bibliography

Search & Optimise

Main features:

• Over 20,000 references to published papers

• by over 20,000 researchers.

• Available as over 70 special bibliographies online:

http://lipas.uwasa.fi/~TAU/reports/report94-1/ga*bib.pdf files.

• Covers all sciences and engineering fields, from basic theory to applica-

tions.

• Several indexes and statistical summaries.

• See what problems evolution can solve for you!

Global optimisation and search heuristics called genetic algorithm mimics evolution in nature usingrecombination and selection from a set of solution trials called population. One of the most prominentattractive features of genetic algorithms from the practical point of view of software techniques is theirsimplicity, which makes them easy to implement and tailor to solve practical search and optimisationproblems.

In spite of the seemingly simple processing, the genetic algorithms are good at solving some problemsthat are known to be hard. The simplicity, generality, flexibility, parallelism, and the good problem solvingcapability have made genetic algorithm very popular among various disciplines desperately searchingmethods to solve difficult optimisation problems.

—————Observe that our server has also a selection of our papers on genetic algorithms and other compuationaltopics. See our bibliographies or file ftp.uwasa.fi/cs/README for further details.



44 Vaasa GA Bibliography

file # refs updated contents

ga90bib.ps.Z GA in 1990...

.

.....

.

..ga02bib.ps.Z 557 GA in 2002gaACOUSTICSbib.pdf 190 2009/08/17 GA in acousticsgaAIbib.pdf 2566 2013/06/14 GA in artificial intelligence

gaAERObib.pdf 911 2014/05/06 GA in aerospacegaAGRObib.pdf 405 2012/08/01 GA in agriculturegaALIFEbib.pdf 184 2014/05/06 GA in artificial lifegaARTbib.pdf 174 2014/05/06 GA in art and musicgaAUSbib.pdf 720 2013/05/14 GA in Australia and New ZealandgaBASICSbib.pdf 1177 2014/04/28 Basics of GAgaBIObib.pdf 1635 2014/05/06 GA in biosciences including medicinegaCADbib.pdf 1407 2012/07/30 GA in Computer Aided DesigngaCHEMbib.pdf 938 2009/07/24 GA in chemical sciences ; previously in gaCHEMPHYSbib.ps.ZgaCHEMPHYSbib.ps.Z 2277 GA in chemistry and physics; divided into gaCHEMbib.ps.Z and gaPHYSbib.ps.Z gaCIVILbib.pdf 1068 2009/01/07 GA in civil, structural, and mechanical engineeringgaCODEbib.pdf 377 2008/03/20 GA codinggaCOEVObib.pdf 232 2008/09/18 co- and differential evolution GAgaCONTROLbib.pdf 1881 2012/08/08 GA in control and process engineeringgaCSbib.pdf 1453 2008/03/20 GA in comp. sci. (incl. databases, /mining, software testing and GP)gaEARLYbib.pdf 723 2014/04/28 GA in early years (upto 1989)

gaEAST-EURObib.ps.Z 679 2003/07/09 GA in the Eastern EuropegaECObib.pdf 1569 2012/07/16 GA in economics and financegaECOLbib.pdf 177 2012/07/16 GA in ecology and biodiversitygaELMAbib.pdf 574 2012/07/20 GA in electromagneticsgaESbib.pdf 464 2008/08/13 Evolution strategiesgaFAR-EASTbib.ps.Z 1556 2011/12/29 GA in the Far East (excl. Japan)gaFEMbib.pdf 90 2014/05/06 GA & FEMgaFINbib.pdf 891 2013/05/22 GA in FinlandgaFPGAbib.pdf 435 2013/11/18 GA & FPGAgaFRAbib.ps.Z 540 2011/12/29 GA in FrancegaFTPbib.ps.Z 1353 2003/07/09 GA papers available via web (ftp and www)gaFUZZYbib.pdf 1521 2012/09/21 GA and fuzzy logicgaGAMEbib.pdf 140 2014/05/06 GA and gamesgaGEObib.pdf 458 2014/05/06 GA in geosciencesgaGERbib.ps.Z 1586 2004/09/22 GA in Germany, Austria, and SwitzerlandgaGPbib.pdf 1006 2012/07/30 genetic programming

gaIMPLEbib.pdf 1500 2012/07/30 implementations of GAgaINDIAbib.ps.Z 276 2003/05/23 GA in IndiagaINVERSEbib.pdf 291 2010/01/08 GA in inverse problemsgaIREGbib.pdf 204 2013/10/28 image registrationgaISbib.pdf 87 2009/08/17 immune systemsgaJAPANbib.ps.Z 2475 2013/05/14 GA in JapangaLCSbib.pdf 211 2012/08/08 Learning Classifier SystemsgaLASERbib.pdf 58 2009/07/31 GA and lasersgaLATINbib.ps.Z 649 2003/07/09 GA in Latin America, Portugal & SpaingaLOGISTICSbib.pdf 741 2014/05/06 GA in logistics (incl. TSP)gaMANUbib.pdf GA in manufacturinggaMATHbib.pdf 846 2009/07/27 GA in mathematicsgaMEDICINEbib.pdf 739 2012/08/01 GA in medicinegaMEDITERbib.ps.Z 1810 2003/07/09 GA in the MediterraneangaMICRObib.pdf 83 2008/03/31 GA in microscopy & microsystemsgaMILbib.pdf 113 2009/08/17 GA in military applicationsgaMLbib.pdf 1231 2012/08/08 GA in machine learninggaMSEbib.pdf 575 2013/08/15 GA in materialsgaNANObib.pdf 117 2012/07/17 GA in nanotechnologygaNIRbib.pdf 267 2013/11/18 GA in NIRS (spectroscopy)gaNNbib.pdf 1883 2012/06/28 GA in neural networksgaNORDICbib.pdf 1125 2013/11/18 GA in Nordic countriesgaOPTICSbib.pdf 2168 2014/04/28 GA in optics and image processinggaOPTIMIbib.pdf 923 2003/07/09 GA and optimization (only a few refs)gaORbib.pdf 1704 2012/07/30 GA in operations research

...table continues on the next page...



Vaasa GA Bibliography 45

file # refs updated contents

gaPARAbib.pdf 833 2012/07/30 Parallel and distributed GAgaPARETObib.pdf 469 2009/03/24 Pareto optimizationgaPATENTbib.pdf 462 2009/07/27 GA patentsgaPATTERNbib.pdf 1654 2012/09/21 GA in pattern recognition incl. LCS

gaPHYSbib.pdf 2313 2008/04/07 GA in physical sciences ; previously in gaCHEMPHYSbib.ps.ZgaPIEZObib.pdf 57 2012/07/18 GA & piezogaPOWERbib.pdf 976 2012/06/28 GA in power engineeringgaPROTEINbib.pdf 491 2008/03/12 GA in protein researchgaPSObib.pdf 92 2013/08/15 Particle Swarm OptimisationgaQCbib.pdf 547 2011/03/09 quantum computinggaREMOTEbib.pdf 302 2012/07/20 GA in remote sensinggaROBOTbib.pdf 775 2009/07/27 GA in roboticsgaSAbib.pdf 331 2009/07/24 GA and simulated annealinggaSCHEDULINGbib.pdf 862 2011/12/29 GA in schedulinggaSELECTIONbib.ps.Z 295 2009/07/27 Selection in GAsgaSIGNALbib.pdf 2587 2012/07/27 GA in signal and image processinggaSIMULAbib.pdf 1037 2009/07/24 GA in simulationgaTELEbib.pdf 840 2009/07/27 GA in telecomgaTHEORYbib.pdf 2654 2012/09/17 Theory and analysis of GAgaTHESESbib.pdf 578 2009/01/07 PhD etc theses

gaVAASAbib.pdf 284 2010/08/17 GA in VaasagaVLSIbib.pdf 799 2012/07/16 GA in electronics, VLSI design and testinggaUKbib.ps.Z 1998 2008/05/22 GA in United KingdomgaXbib.ps.Z 129 2013/08/15 GA & X-rays

Table B.1: Indexed genetic algorithm special bibliographies available online in directoryhttp://lipas.uwasa.fi/~TAU/reports/report94-1. New updates only as .pdf files.

bibliography of genetic algorithms in arts and music

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