Solving Very Difficult Japanese Puzzles with a Hybrid Evolutionary-Logic Algorithm

  • Emilio G. Ortiz-García
  • Sancho Salcedo-Sanz
  • Ángel M. Pérez-Bellido
  • Antonio Portilla-Figueras
  • Xin Yao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5361)

Abstract

In this paper we present a hybrid evolutionary algorithm to solve a popular logic-type puzzle, the so called Japanese puzzle. We propose to use the evolutionary algorithm in order to initialize a logic ad-hoc algorithm, which works as a local search and implicitly defines the fitness function of the problem. Two novel operators, one for initializing the evolutionary algorithm and a second one providing a novel type of mutation adapted to Japanese puzzles are described in the paper.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Conceptis Puzzles Inc., http://www.conceptispuzzles.com
  2. 2.
  3. 3.
    Dorant, M.: A begginer’s guide to solving picture forming logic puzzles, http://www.conceptispuzzles.com/index.aspx?uri=info/article/79
  4. 4.
    Ueda, N., Nagao, T.: NP-completeness results for nonograms via parsimonious reductions. Internal Report, University of Tokyo, Computer Science Department (1996)Google Scholar
  5. 5.
    Benton, J., Snow, R., Wallach, N.: A combinatorial problem associated with nonograms. Linear Algebra and its Applications 412(1), 30–38 (2006)MathSciNetCrossRefMATHGoogle Scholar
  6. 6.
    Salcedo-Sanz, S., Ortiz-García, E., PérezBellido, A., Portilla-Figueras, J., Yao, X.: Solving Japanese Puzzles with Heuristics. In: IEEE Symposium on Computational Intelligence and Games, Honolulu, USA (April 2007)Google Scholar
  7. 7.
    Ortiz-García, E., Salcedo-Sanz, S., Leiva-Murillo, J.M., PérezBellido, A., Portilla-Figueras, J.: Automated generation and visualization of picture-logic puzzles. Computers & Graphics 31, 750–760 (2007)CrossRefGoogle Scholar
  8. 8.
    Batenburg, B., Kosters, W.: A discrete tomography approach to Japanese puzzles. In: Proceedings of the Belgian-Dutch Conference on Artificial Intelligence, pp. 243–250 (2004)Google Scholar
  9. 9.
    Wiggers, W.: A comparison of a genetic algorithm and a depth first search algorithm applied to Japanese nonograms. In: Proceedings of the 1st Twente Student Conference on IT, pp. 1–6 (2004)Google Scholar
  10. 10.
    Salcedo-Sanz, S., Portilla-Figueras, J., PérezBellido, A., Ortiz-García, E., Yao, X.: Teaching advanced features of evolutionary algorithms using Japanese puzzles. IEEE Transactions on Education 50(2), 151–155 (2007)CrossRefGoogle Scholar
  11. 11.
    Duncan, G.: Puzzle Soving. B.Sc. Degree Final Project Report, University of York, Computer Science Department (1999)Google Scholar
  12. 12.
    Simpson, S.: http://www.comp.lancs.ac.uk\computing\users\ss\nonogram\index.htmlGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Emilio G. Ortiz-García
    • 1
  • Sancho Salcedo-Sanz
    • 1
  • Ángel M. Pérez-Bellido
    • 1
  • Antonio Portilla-Figueras
    • 1
  • Xin Yao
    • 2
  1. 1.Department of Signal Theory and CommunicationsUniversidad de AlcaláMadridSpain
  2. 2.The Centre for Research in Computational Intelligence and Applications (CERCIA), School of Computer ScienceThe University of Birmingham, Birmingham, U.K. and Nature Inspired Computation and Applications Laboratory (NICAL), University of Science and Technology of ChinaHefeiP.R. China

Personalised recommendations