Advertisement

Cumulation of Pheromone Values in Web Searching Algorithm

  • Urszula Boryczka
  • Iwona Polak
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 59)

Abstract

In this paper, we propose a new ant-based searching algorithm called Seangàn. We describe a process of stigmergy and accumulation of pheromone values, leading to a degree of self-organization brought about through the independent actions and iterations of its individual agents. We use it in the construction in our continually evolving system, Seangàn. We discuss some of the issues raised and attempt to explain some of its success as well as account for its failings. We analyze the main characteristics of the algorithm and try to explain the influence of parameters value on the behavior of this system.

Keywords

ant colony optimization stigmergy pheromone cumulation web searching 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bilchev, G., Parmee, I.C.: The ant colony metaphor for searching continuous design spaces. In: Fogarty, T.C. (ed.) AISB-WS 1995. LNCS, vol. 993. Springer, Heidelberg (1995)Google Scholar
  2. 2.
    Bonabeau, E., Dorigo, M., Theraulaz, G.: Swarm Intelligence. From Natural to Artificial Systems. Oxford University Press, Oxford (1999)zbMATHGoogle Scholar
  3. 3.
    Corne, D., Dorigo, M., Glover, F.: New Ideas in Optimization. McGraw-Hill, New York (1999)Google Scholar
  4. 4.
    Deneubourg, J.L.: Personal communication. Université Libre de Bruxelles, Brussels, Belgium (2002)Google Scholar
  5. 5.
    Deneubourg, J.L., Aron, S., Goss, S., Pasteels, J.M.: The self–organizing exploratory pattern of the Argentine ant. Journal of Insect Behavior 3, 159–168 (1990)CrossRefGoogle Scholar
  6. 6.
    Dorigo, M., Gambardella, L.M.: Ant colonies for the Traveling Salesman Problem. Biosystems 43, 73–81 (1997)CrossRefGoogle Scholar
  7. 7.
    Dorigo, M., Stützle, T.: Ant Colony Optimization. The Massetchussets Institute of Technology Press (2004)Google Scholar
  8. 8.
    Goss, S., Aron, S., Deneubourg, J.L., Pasteels, J.M.: Self–organized shortcuts in the Argentine ant. Naturwissenschaften 76, 579–581 (1989)CrossRefGoogle Scholar
  9. 9.
    Passino, K.M.: Biomimicry for Optimization, Control, and Automation. Springer, London (2005)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Urszula Boryczka
    • 1
  • Iwona Polak
    • 1
  1. 1.Institute of Computer ScienceUniversity of SilesiaSosnowiecPoland

Personalised recommendations