Juan J. Merelo
ABSTRACT
The Mastermind puzzle consists in finding out a secret combination by playing others in the same search space and using the hints obtained as a response (which reveal how close the played combination is to the secret one) to produce new combinations and eventually the secret one. Despite having been researched for a number of years, there are still several open issues, such as finding a strategy to select the next combination to play that is able to consistently obtain good results, at any problem size, and also doing it in as little time as possible. In this paper we cast this as a constrained optimization problem, introducing a new fitness function for evolutionary algorithms that takes that fact into account, and compare it to other solutions (exhaustive/heuristic and evolutionary), finding that it is able to obtain the consistently good solutions, and in as little as 30% less time than previously published evolutionary algorithms [2].
- Juan-Julián Merelo and Thomas P. Runarsson. Finding better solutions to the mastermind puzzle using evolutionary algorithms. volume 6024 of Lecture Notes in Computer Science, pages 120--129, Istanbul, Turkey, 7 - 9 April 2010. Springer-Verlag. EvoApplications2010 to be held in conjunction with EuroGP-2010, EvoCOP2010 and EvoBIO2010. To appear.Google Scholar
- Eric W. Weisstein. Mastermind. From MathWorld-A Wolfram Web Resource.Google Scholar
- B. Kooi. Yet another Mastermind strategy. ICGA Journal,28(1):13--20, 2005.Google ScholarCross Ref
- L. Berghman, D. Goossens, and R. Leus. Efficient solutions for Mastermind using genetic algorithms. Computers and Operations Research, 36(6):1880--1885, 2009. Google ScholarDigital Library
- T. P Runarsson and J. J. Merelo. Adapting heuristic Mastermind strategies to evolutionary algorithms. In NICSO'10 Proceedings, LNCS. Springer-Verlag, 2010. To be published, also available from ArXiV: http://arxiv.org/abs/0912.2415v1.Google ScholarCross Ref
Index Terms
- Beating exhaustive search at its own game: revisiting evolutionary mastermind
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