Ant Colonies Discover Knight’s Tours

  • Philip Hingston
  • Graham Kendall
Conference paper

DOI: 10.1007/978-3-540-30549-1_125

Part of the Lecture Notes in Computer Science book series (LNCS, volume 3339)
Cite this paper as:
Hingston P., Kendall G. (2004) Ant Colonies Discover Knight’s Tours. In: Webb G.I., Yu X. (eds) AI 2004: Advances in Artificial Intelligence. AI 2004. Lecture Notes in Computer Science, vol 3339. Springer, Berlin, Heidelberg


In this paper we introduce an Ant Colony Optimisation (ACO) algorithm to find solutions for the well-known Knight’s Tour problem. The algorithm utilizes the implicit parallelism of ACO’s to simultaneously search for tours starting from all positions on the chessboard. We compare the new algorithm to a recently reported genetic algorithm, and to a depth-first backtracking search using Warnsdorff’s heuristic. The new algorithm is superior in terms of search bias and also in terms of the rate of finding solutions.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Philip Hingston
    • 1
  • Graham Kendall
    • 2
  1. 1.Edith Cowan UniversityAustralia
  2. 2.The University of NottinghamUK

Personalised recommendations