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.
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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.
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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
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DOI: https://doi.org/10.1007/978-3-642-44973-4_31
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