Abstract
There are two main research issues in the game of Mastermind: one of them is finding solutions that are able to minimize the number of turns needed to find the solution, and another is finding methods that scale well when the size of the search space is increased. In this paper we will present a method that uses evolutionary algorithms to find fast solutions to the game of Mastermind that scale better with problem size than previously described methods; this is obtained by just fixing one parameter.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Meirovitz, M.: Board game (December 30 1980) US Patent 4,241,923
Knuth, D.E.: The computer as master mind. J. Recreational Math. 9(1), 1–6 (1976–1977)
Montgomery, G.: Mastermind: improving the search. AI Expert 7(4), 40–47 (1992)
Berghman, L., Goossens, D., Leus, R.: Efficient solutions for mastermind using genetic algorithms. Compu. Oper. Res. 36(6), 1880–1885 (2009)
Runarsson, T.P., Merelo-Guervós, J.J.: Adapting heuristic mastermind strategies to evolutionary algorithms. In: González, J.R., Pelta, D.A., Cruz, C., Terrazas, G., Krasnogor, N. (eds.) NICSO 2010. SCI, vol. 284, pp. 255–267. Springer, Heidelberg (2010). ArXiV: http://arxiv.org/abs/0912.2415v1
Merelo-Guervós, J.J., Mora, A.M., Cotta, C., Runarsson, T.P.: An experimental study of exhaustive solutions for the mastermind puzzle. CoRR abs/1207.1315 (2012)
Kooi, B.: Yet another mastermind strategy. ICGA J. 28(1), 13–20 (2005)
Cotta, C., Merelo Guervós, J.J., Mora Garćia, A.M., Runarsson, T.P.: Entropy-driven evolutionary approaches to the mastermind problem. In: Schaefer, R., Cotta, C., Kołodziej, J., Rudolph, G. (eds.) PPSN XI. LNCS, vol. 6239, pp. 421–431. Springer, Heidelberg (2010)
Merelo, J., Mora, A., Runarsson, T., Cotta, C.: Assessing efficiency of different evolutionary strategies playing mastermind. In: 2010 IEEE Symposium on Computational Intelligence and Games (CIG), pp. 38–45, August 2010
Merelo, J.J., Cotta, C., Mora, A.: Improving and scaling evolutionary approaches to the mastermind problem. In: Di Chio, C., et al. (eds.) EvoApplications 2011, Part I. LNCS, vol. 6624, pp. 103–112. Springer, Heidelberg (2011)
Merelo-Guervós, J.J., Mora, A.M., Cotta, C.: Optimizing worst-case scenario in evolutionary solutions to the MasterMind puzzle. In: IEEE Congress on Evolutionary Computation, pp. 2669–2676. IEEE (2011)
Eiben, A.E., Smit, J.E.: Introduction to Evolutionary Computing. Springer, Heidelberg (2003)
Acknowledgements.
This work is supported by projects TIN2011-28627-C04-02 and TIN2011-28627-C04-01 and -02 (ANYSELF), awarded by the Spanish Ministry of Science and Innovation and P08-TIC-03903 and P10-TIC-6083 (DNEMESIS) awarded by the Andalusian Regional Government.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Merelo, J.J., Mora, A.M., Cotta, C., Fernández-Leiva, A.J. (2013). Finding an Evolutionary Solution to the Game of Mastermind with Good Scaling Behavior. In: Nicosia, G., Pardalos, P. (eds) Learning and Intelligent Optimization. LION 2013. Lecture Notes in Computer Science(), vol 7997. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-44973-4_31
Download citation
DOI: https://doi.org/10.1007/978-3-642-44973-4_31
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-44972-7
Online ISBN: 978-3-642-44973-4
eBook Packages: Computer ScienceComputer Science (R0)