Towards creative evolutionary systems with interactive genetic algorithm: Unterschied zwischen den Versionen
(Die Seite wurde neu angelegt: „ == Reference == Cho, S.B. (2002). Towards creative evolutionary systems with interactive genetic algorithm. Applied Intelligence, 16(2): 129–138. == DOI =…“) |
(→Used References) |
||
| Zeile 31: | Zeile 31: | ||
J.-Y. Lee and S.-B. Cho, “Interactive genetic algorithm for content-based image retrieval,” in Proc. Asia Fuzzy Systems Symposium, 1998, pp. 479–484. | J.-Y. Lee and S.-B. Cho, “Interactive genetic algorithm for content-based image retrieval,” in Proc. Asia Fuzzy Systems Symposium, 1998, pp. 479–484. | ||
| − | Cyberware Inc., http://ghiberti.cyberware.com. | + | Cyberware Inc., http://ghiberti.cyberware.com. 404 |
S. Gray, “In virtual fashion,” IEEE Spectrum, vol. 35, no. 2, pp. 19–25, 1998. | S. Gray, “In virtual fashion,” IEEE Spectrum, vol. 35, no. 2, pp. 19–25, 1998. | ||
| Zeile 50: | Zeile 50: | ||
C.E. Jacobs, A. Findkelstein, and D.H. Salesin, “Fast multiresolution image querying,” in Proc. SIGGRAPH 95, 1995. | C.E. Jacobs, A. Findkelstein, and D.H. Salesin, “Fast multiresolution image querying,” in Proc. SIGGRAPH 95, 1995. | ||
| − | |||
== Links == | == Links == | ||
Aktuelle Version vom 13. November 2014, 20:09 Uhr
Inhaltsverzeichnis
Reference
Cho, S.B. (2002). Towards creative evolutionary systems with interactive genetic algorithm. Applied Intelligence, 16(2): 129–138.
DOI
http://link.springer.com/article/10.1023%2FA%3A1013614519179
Abstract
Evolutionary computation has shown a great potential to work out several real-world problems in the point of optimization, but it is still quite far from realizing a system of matching the human performance. Especially, in creative applications such as architecture, art, music, and design, it is difficult to evaluate the fitness because the measure depends mainly on the human mind. To overcome this shortcoming, this paper presents a novel technique, called interactive genetic algorithm (IGA), which performs optimization with human evaluation and the user can obtain what he has in mind through repeated interaction with. To show the usefulness of the IGA to develop effective human-oriented evolutionary systems, we have applied it to the problems of fashion design and emotion-based image retrieval. Experiments with several human subjects indicate that the IGA approach is promising to develop creative evolutionary systems.
Extended Abstract
Bibtex
Used References
D.E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley: Reading, MA, 1989.
M. Srinivas and L.M. Patnaik, “Genetic algorithms: A survey,” IEEE Computer, vol. 27, no. 6, pp. 17–26, 1994.
J.A. Biles, “GenJam: A genetic algorithm for generating jazz solos,” in Proc. Int. Computer Music Conf., Aarhus, Denmark, 1994, pp. 131–137.
C. Caldwell and V.S. Johnston, “Tracking a criminal suspect through face-space with a genetic algorithm,” in Proc. 4th Int. Conf. Genetic Algorithm, 1991, Morgan Kaufmann: San Mateo, CA, pp. 416–421.
Y. Nakanishi, “Capturing preference into a function using interactions with a manual evolutionary design aid system,” in Genetic Programming, 1996, Late-Breaking Papers, 1996, pp. 133–138.
H. Takagi, “Interactive evolutionary computation: Fusion of the capabilities of EC optimization and human evaluation,” Proc. of the IEEE, vol. 89, no. 9, pp. 1275–1296, 2001.
W. Banzhaf, “Interactive evolution,” Handbook of Evolutionary Computation, 1997.
J.-Y. Lee and S.-B. Cho, “Interactive genetic algorithm for content-based image retrieval,” in Proc. Asia Fuzzy Systems Symposium, 1998, pp. 479–484.
Cyberware Inc., http://ghiberti.cyberware.com. 404
S. Gray, “In virtual fashion,” IEEE Spectrum, vol. 35, no. 2, pp. 19–25, 1998.
R.S. Wright and M. Sweet, OpenGL Superbible, Waite Group Press, 1996.
A.L. Ames, D.R. Nadeau, and J.L. Moreland, VRML 2.0 Sourcebook, John Wiley: New York, 1996.
M.J. Kilgard, The OpenGL Utility Toolkit (GLUT) Programming Interface API Version 3, Silicon Graphics, Inc., http:// reality.sgi.com/mjk asd/spec3/spec3.html.
H.A. David, The Method of Paired Comparison, Charles Griffin, 1969.
W. Niblack et al., “The QBIC project: Querying images by content using color, texture, and shape,” in Storage and Retrieval for Image and Video Databases, SPIE, pp. 173–187, 1993.
K. Hirata and T. Kato, “Query by visual example: Content based image retrieval,” Advances in Database Technology, EDBT '92, pp. 56–61, 1992.
V.E. Ogel and M. Stonebraker, “Chabot: Retrieval from a relational database of images,” IEEE Computer, vol. 28, no. 9, pp. 40–48, 1995.
C.E. Jacobs, A. Findkelstein, and D.H. Salesin, “Fast multiresolution image querying,” in Proc. SIGGRAPH 95, 1995.
Links
Full Text
http://candy.yonsei.ac.kr/publications/Papers/TCESIGA.pdf
