Skip to main content

On the Treewidth of NK Landscapes

  • Conference paper
  • First Online:
Genetic and Evolutionary Computation — GECCO 2003 (GECCO 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2723))

Included in the following conference series:

  • 1519 Accesses

Abstract

The concepts of treewidth and tree-decomposition on graphs generalize those of the trees. It is well established that when restricted to instances with a bounded treewidth, many NP hard problems can be solved polynomially. In this paper, we study the treewidth of the NK landscape models. We show that the NK landscape model with adjacent neighborhoods has a constant treewidth, and prove that for κ ≥ 2, the treewidth of the NK landscape model with random neighborhoods asymptotically grows with the problem size n.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Kauffman, S.: The Origins of Order: Self-organization and Selection in Evolution. Oxford University Press, Inc. (1993)

    Google Scholar 

  2. Weinberger, E.D.: NP completeness of Kauffman’s NK model, a tunable rugged fitness landscape. Technical Report Working Papers 96-02-003, Santa Fe Institute, Santa Fe (1996)

    Google Scholar 

  3. Wright, A.H., Thompson, R.K., Zhang, J.: The computational complexity of NK fitness functions. Technical report, Department of Computer Science, University of Montana (1999)

    Google Scholar 

  4. Gao, Y., Culberson, J.: An analysis of phase transition in NK landscapes. Journal of Artificial Intelligence Research 17 (2002) 309–332

    MATH  MathSciNet  Google Scholar 

  5. Evans, S.N., Steinsaltz, D.: Estimating some features of NK fitness landscapes. Ann. Appl. Probab. 12 (2002) 1299–1321

    Article  MATH  MathSciNet  Google Scholar 

  6. Dechter, R., Fattah, Y.: Topological parameters for time-space tradeoff. Artificial Intelligence 125 (2001) 93–118

    Article  MATH  MathSciNet  Google Scholar 

  7. Kloks, T.: Treewidth: Computations and Approximations. Springer-Verlag (1994)

    Google Scholar 

  8. Downey, R.G., Fellows, M.R.: Parameterized Complexity. Springer (1997)

    Google Scholar 

  9. Gottlob, G., Leone, N., Scarcello, F.: A comparison of structural CSP decomposition methods. Articial Intelligence 124 (2000) 243–282

    Article  MATH  MathSciNet  Google Scholar 

  10. Leung, Y., Gao, Y., Zhang, W.: A genetic-based method for training fuzzy systems. In: Proc. of the 10th IEEE International Conference on Fuzzy Systems. Volume 1., IEEE (2001) 123–126

    Google Scholar 

  11. Mühlenbein, H., Mahnig, T.: Convergence theory and applications of the factorized distribution algorithm. Journal of Computing and Information Technology 7 (1999) 19–32

    Google Scholar 

  12. Pelikan, M., Goldberg, D.E., Lobo, F.: A survey of optimization by building and using probabilistic models. Technical Report 99018, IlliGAL, University of Illinois (1999)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2003 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Gao, Y., Culberson, J. (2003). On the Treewidth of NK Landscapes. In: Cantú-Paz, E., et al. Genetic and Evolutionary Computation — GECCO 2003. GECCO 2003. Lecture Notes in Computer Science, vol 2723. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45105-6_106

Download citation

  • DOI: https://doi.org/10.1007/3-540-45105-6_106

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40602-0

  • Online ISBN: 978-3-540-45105-1

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics