Generative Representations for Evolving Families of Designs

Aus de_evolutionary_art_org
Version vom 22. November 2014, 14:38 Uhr von Gbachelier (Diskussion | Beiträge) (Die Seite wurde neu angelegt: „ == Reference == Gregory S. Hornby: Generative Representations for Evolving Families of Designs. Genetic and Evolutionary Computation – GECCO-2003, LNCS, Vo…“)

(Unterschied) ← Nächstältere Version | Aktuelle Version (Unterschied) | Nächstjüngere Version → (Unterschied)
Wechseln zu: Navigation, Suche


Reference

Gregory S. Hornby: Generative Representations for Evolving Families of Designs. Genetic and Evolutionary Computation – GECCO-2003, LNCS, Vol. 2724, pp. 1678-1689, Springer-Verlag, 12-16 July 2003.

DOI

http://link.springer.com/chapter/10.1007%2F3-540-45110-2_61

Abstract

Since typical evolutionary design systems encode only a single artifact with each individual, each time the objective changes a new set of individuals must be evolved. When this objective varies in a way that can be parameterized, a more general method is to use a representation in which a single individual encodes an entire class of artifacts. In addition to saving time by preventing the need for multiple evolutionary runs, the evolution of parameter-controlled designs can create families of artifacts with the same style and a reuse of parts between members of the family. In this paper an evolutionary design system is described which uses a generative representation to encode families of designs. Because a generative representation is an algorithmic encoding of a design, its input parameters are a way to control aspects of the design it generates. By evaluating individuals multiple times with different input parameters the evolutionary design system creates individuals in which the input parameter controls specific aspects of a design. This system is demonstrated on two design substrates: neural-networks which solve the 3/5/7-parity problem and three-dimensional tables of varying heights.

Extended Abstract

Bibtex

Used References

Gruau, F.: Neural Network Synthesis Using Cellular Encoding and the Genetic Algorithm. PhD thesis, Ecole Normale Supérieure de Lyon (1994)

Dawkins, R.: The Blind Watchmaker. Harlow Longman (1986)

Ventrella, J.: Explorations in the emergence of morphology and locomotion behavior in animated characters. In Brooks, R., Maes, P., eds.: Proceedings of the Fourth Workshop on Artificial Life, Boston, MA, MIT Press (1994)

de Garis, H.: Artificial embryology: The genetic programming of an artificial embryo. In Soucek, B., the IRIS Group, eds.: Dynamic, Genetic and Chaotic Programming, Wiley (1992)

Bonabeau, E., Gu rin, S., Snyers, D., Kuntz, P., Theraulaz, G.: Three-dimensional architectures grown by simple’ stigmergic’ agents. BioSystems 56 (2000) 13–32 http://dx.doi.org/10.1016/S0303-2647(00)00067-8

Ochoa, G.: On genetic algorithms and lindenmayer systems. In Eiben, A., Baeck, T., Schoenauer, M., Schwefel, H.P., eds.: Parallel Problem Solving from Nature V, Springer-Verlag (1998) 335–344

Coates, P., Broughton, T., Jackson, H.: Exploring three-dimensional design worlds using lindenmayer systems and genetic programming. In Bentley, P.J., ed.: Evolutionary Design by Computers. (1999)

Frazer, J.: An Evolutionary Architecture. Architectural Association Publications (1995)

Jacob, C.: Genetic L-system Programming. In Davidor, Y., Schwefel, P., eds.: Parallel Problem Solving from Nature III, Lecture Notes in Computer Science. Volume 866. (1994) 334–343

Hornby, G.S.: Generative Representations for Evolutionary Design Automation. PhD thesis, Michtom School of Computer Science, Brandeis University, Waltham, MA (2003)

Prusinkiewicz, P., Lindenmayer, A.: The Algorithmic Beauty of Plants. Springer-Verlag (1990)

Bäck, T.: Evolutionary Algorithms in Theory and Practice. Oxford University Press, New York (1996)

Michalewicz, Z.: Genetic Algorithms + Data Structures = Evolution Programs. Springer-Verlag, New York (1992)

Koza, J.R.: Genetic Programming: on the programming of computers by means of natural selection. MIT Press, Cambridge, Mass. (1992)

Hornby, G.S., Pollack, J.B.: Creating high-level components with a generative representation for body-brain evolution. Artificial Life 8 (2002) 223–246 http://dx.doi.org/10.1162/106454602320991837

Hornby, G.S., Pollack, J.B.: The advantages of generative grammatical encodings for physical design. In: Congress on Evolutionary Computation. (2001) 600–607


Links

Full Text

http://idesign.ucsc.edu/papers/hornby_gecco03.pdf

intern file

Sonstige Links