NK landscapes difficulty and negative slope coefficient: How sampling influences the results

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5484 LNCS, Issue , 2009, Pages 645-654

  Vanneschi, Leonardo ^a   Verel, Sébastien ^b   Tomassini, Marco ^c   Collard, Philippe ^b  

^a UNIVERSITY OF MILANO BICOCCA   (Italy)

^b UNIVERSITY OF NICE SOPHIA ANTIPOLIS   (France)

^c UNIVERSITY OF LAUSANNE   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

FITNESS LANDSCAPE; NEGATIVE SLOPE; POTENTIAL PROBLEMS;

COMPUTER SCIENCE;

BINS;

EID: 67650679606     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-01129-0_74     Document Type: Conference Paper

References (13)

1. Aguirre, H.E., Tanaka, K.: Genetic algorithms on NK-landscapes: Effects of selection, drift, mutation, and recombination. In: Raidl, G.R., Cagnoni, S., Cardalda, J.J.R., Corne, D.W., Gottlieb, J., Guillot, A., Hart, E., Johnson, C.G.,Marchiori, E., Meyer, J.-A., Middendorf, M. (eds.) EvoIASP 2003, EvoWorkshops 2003, EvoSTIM2003, EvoROB/EvoRobot 2003, Evo- COP 2003, EvoBIO 2003, and EvoMUSART 2003. LNCS, vol.2611, pp. 131-142. Springer, Heidelberg (2003) (Pubitemid 36571931)
2. Jones, T., Forrest, S.: Fitness distance correlation as a measure of problem difficulty for genetic algorithms. In: Eshelman, L.J. (ed.) Proceedings of the Sixth International Conference on Genetic Algorithms, pp. 184-192. Morgan Kaufmann, San Francisco (1995)
3. Kallel, L., Naudts, B., Rogers, A. (eds.): Theoretical Aspects of Evolutionary Computing. Springer, Heidelberg (2001)
4. Kauffman, S.A.: The Origins of Order. Oxford University Press, New York (1993)
5. Madras, N.: Lectures on Monte Carlo Methods. American Mathematical Society, Providence (2002)
6. Poli, R., Vanneschi, L.: Fitness-proportional negative slope coefficient as a hardness measure for genetic algorithms. In: Thierens, D., et al. (eds.) Genetic and Evolutionary Computation Conference, GECCO 2007, pp. 1335-1342. ACM Press, New York (2007) (Pubitemid 47291700)
7. Rośe, H., Ebeling, W., Asselmeyer, T.: The density of states - a measure of the difficulty of optimisation problems. In: Ebeling, W., Rechenberg, I., Voigt, H.-M., Schwefel, H.-P. (eds.) PPSN 1996. LNCS, vol.1141, pp. 208-217. Springer, Heidelberg (1996) (Pubitemid 126128309)
8. Tomassini, M., Vanneschi, L.: Negative slope coefficient and the difficulty of random 3-sat instances. In: Giacobini, M., et al. (eds.) EvoWorkshops 2008. LNCS, vol.4974, pp. 643- 648. Springer, Heidelberg (2008)
9. Vanneschi, L.: Theory and Practice for Efficient Genetic Programming. Ph.D. thesis, Faculty of Science, University of Lausanne, Switzerland (2004), http://www.disco.unimib.it/vanneschi
10. Vanneschi, L., Clergue, M., Collard, P., Tomassini, M., V́erel, S.: Fitness clouds and problem hardness in genetic programming. In: Deb, K., et al. (eds.) GECCO 2004. LNCS, vol.3103, pp. 690-701. Springer, Heidelberg (2004) (Pubitemid 39740121)
11. Vanneschi, L., Tomassini, M., Collard, P., V́erel, S.: Negative slope coefficient: A measure to characterize genetic programming fitness landscapes. In: Collet, P., et al. (eds.) EuroGP 2006. LNCS, vol.3905, pp. 178-189. Springer, Heidelberg (2006) (Pubitemid 44011478)
12. V́erel, S., Collard, P., Clergue, M.: Where are bottleneck in NK fitness landscapes? In: CEC 2003: IEEE International Congress on Evolutionary Computation, Canberra, Australia, pp. 273-280. IEEE Press, Piscataway (2003)
13. Weinberger, E.D.: Correlated and uncorrelated fitness landscapes and how to tell the difference. Biol. Cybern. 63, 325-336 (1990) (Pubitemid 20289470)