Abstract
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. © Springer-Verlag Berlin Heidelberg 2004.
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CITATION STYLE
Hingston, P., & Kendall, G. (2004). Ant colonies discover Knight’s Tours. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 3339, pp. 1213–1218). Springer Verlag. https://doi.org/10.1007/978-3-540-30549-1_125
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