Optimizing genetic algorithm strategies for evolving networks

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 5473, Issue , 2004, Pages 122-130

  Berryman, Matthew J ^a   Allison, Andrew ^a   Abbott, Derek ^a  

^a UNIVERSITY OF ADELAIDE   (Australia)

Author keywords

Genetic algorithms; Networks; Pleiotropy; Redundancy

Indexed keywords

EVOLUTIONARY COMPUTATIONAL TECHNIQUES; EVOLUTIONARY NETWORKS; NETWORK DESIGNS; PLEIOTROPY;

COMPUTATIONAL COMPLEXITY; CONSTRAINT THEORY; MUTAGENESIS; OPTIMIZATION; REDUNDANCY; SEARCH ENGINES; SERVERS;

GENETIC ALGORITHMS;

EID: 4344669097     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.548122     Document Type: Conference Paper

References (17)

1. P. H. Winston, Artificial Intelligence, 3rd Ed., Addison Wesley, 1993.
2. J. H. Holland, "Outline for a logical theory of adaptive systems,"Journal of the Association for Computing Machinery 9(3), pp. 297-314, 1962.
3. M. Mitchell, An Introduction to Genetic Algorithms, MIT Press, 1996.
4. D. B. Fogel, "What is evolutionary computation,"IEEE Spectrum 37(2), 2000.
5. M. Mitchell, J. H. Holland, and S. Forrest, "When will a genetic algorithm outperform hill climbing,"in Advances in Neural Information Processing Systems, J. Cowan, G. Tesauro, and J. Alspector, eds., 6, pp. 51-58, Morgan Kaufmann Publishers, Inc., 1994.
6. M. Mitchell and S. Forrest, "Fitness landscapes: royal road functions,"in Handbook of Evolutionary Computation, T. Bäck, D. Fogel, and Z. Michalewicz, eds., pp. B.2.7.5:1-25, Oxford University Press, 1997.
7. M. J. Berryman, W.-L. Khoo, H. Nguyen, E. O'Neill, A. Allison, and D. Abbott, "Exploring tradeoffs in pleiotropy and redundancy using evolutionary computing,"in Proc. SPIE: BioMEMS and Nanotechnology, D. Nicolau, ed., 5275, p. in press, 2003.
8. R. K. Belew, J. McInerney, and N. N. Schraudolph, "Evolving networks: using the genetic algorithm with connectionist learning,"in Proc. Second Conference on Artificial Life, C. Langton, C. Taylor, J. Farmer, and S. Rasmussen, eds., pp. 511-547, Addison-Wesley, 1991.
9. F. Gruau and D. Whitley, "Adding learning to the cellular development of neural networks: Evolution and the baldwin effect, "Evolutionary Computation 1(3), pp. 213-233, 1993.
10. I. de Falco, A. Iazzetta, P. Natale, and E. Tarantino, "Evolutionary neural networks for nonlinear dynamics modeling,"Lecture notes in computer science 1498, pp. 593-602, 1998.
11. A. Abuali, W. Wainwright, and D. Schoenfeld, "Determinant factorization: a new encoding scheme for spanning trees applied to the probabilistic minimum spanning tree problem,"in Proc. Sifth Intl. Conf. on Genetic Algorithms, pp. 470-477, 1995.
12. H. Sayoud and K. Takahashi, "Designing communication network topologies using steady-state genetic algorithms,"IEEE Communications Letters 5(3), pp. 113-115, 2001.
13. T. L. Hoo, A. Ting, E. O'Neill, A. Allison, and D. Abbott, "Real life: a cellular automaton for investigating competition between pleiotropy and redundancy,"in Proc. SPIE: Electronics and Structures for MEMS II, N. Bergmann, ed., 4591, pp. 380-389, 2001.
14. S. N. Coppersmith, R. D. Black, and L. P. Kadanoff, "Analysis of a population genetics model with mutations, selection, and pleiotropy,"J. Statistical Physics 97, pp. 429-457, 1999.
15. M. Morange, "Gene function,"C.R. Acad. Sci. III 323, pp. 1147-1153, 2000.
16. E. Dijkstra, "A note on two problems in connection with graphs,"Numeriche Mathematik 1, pp. 269-271, 1959.
17. P. Narváez, K.-Y. Siu, and H.-Y. Tzen, "New dynamic algorithms for shortest path tree computation,"IEEE/ACM Trans. Networking 8, pp. 734-746, Dec. 2000.