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Application of Hopfield Neural Network to the N-Queens Problem

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Biologically Inspired Cognitive Architectures (BICA) for Young Scientists

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 449))

Abstract

This paper describes one of the methods to use Hopfield neural network in combinatorial optimization. This subject has many problems and one of them is the N-Queens problem. The algorithm for solving this problem is written in Matlab and the results can be shown as an N × N chessboard with N-Queens.

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References

  1. Hopfield, J.J.: Neurons with graded response have collective computational properties like those of two-state neurons. Proc. Nat. Acad. Sci. USA 81, 3088–3092 (1984)

    Article  Google Scholar 

  2. Hopfield Network, https://en.wikipedia.org/wiki/Hopfield_network

  3. Durango Bill’s “N-Queens Problem”, http://www.durangobill.com/N-Queens.html

  4. Melanie, M.: An Introduction to Genetic Algorithms. MIT Press, Massachusetts (1999)

    MATH  Google Scholar 

  5. Božikovic, M., Golub, M., Budin, L.: Solving N-Queen problem using global parallel genetic algorithm. In: EUROCON. Ljubljana, Slovenia (2003)

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  6. Lyapunov, A.M.: General problem on stability of motion (English translation). London, Taylors and Francis (1992)

    Google Scholar 

  7. Feng G., Douligeris C.: Using Hopfield networks to solve assignment problem and N-Queen problem: an application of guided trial and error technique. Proceeding of the 2nd Hellenic Conference on Artificial Intelligence SETN, pp. 325–336 (2002)

    Google Scholar 

  8. Galan-Marin, G., Munoz-Perez, J.: Design and analysis of maximum Hopfield networks. IEEE Trans. Neural Netw. 12(2), 329–339 (2001)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Control in Technical Systems, Saint-Petersburg State University of Aerospace Instrumentation, Saint Petersburg, Russia

    Andrei A. Lapushkin

Authors
  1. Andrei A. Lapushkin
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Correspondence to Andrei A. Lapushkin .

Editor information

Editors and Affiliations

  1. Department 22 “Cybernetics”, National Research Nuclear University, Moscow, Russia

    Alexei V. Samsonovich

  2. “MEPhI”, National Research Nuclear University, Moscow, Russia

    Valentin V. Klimov

  3. “MEPhI”, National Research Nuclear University, Moscow, Russia

    Galina V. Rybina

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Lapushkin, A.A. (2016). Application of Hopfield Neural Network to the N-Queens Problem. In: Samsonovich, A., Klimov, V., Rybina, G. (eds) Biologically Inspired Cognitive Architectures (BICA) for Young Scientists . Advances in Intelligent Systems and Computing, vol 449. Springer, Cham. https://doi.org/10.1007/978-3-319-32554-5_15

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  • DOI: https://doi.org/10.1007/978-3-319-32554-5_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-32553-8

  • Online ISBN: 978-3-319-32554-5

  • eBook Packages: EngineeringEngineering (R0)

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