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A heuristic hill climbing algorithm for mastermind

Alexandre Temporel, Tim Kovacs, A heuristic hill climbing algorithm for mastermind. Proceedings of the 2003 UK Workshop on Computational Intelligence (UKCI-03). ISSN 0862925371, pp. 189–196. September 2003. PDF, 109 Kbytes.

Abstract

The game of Mastermind is a constraint optimisation problem. There are two aspects which seem interesting to minimise. The first is the number of guesses needed to discover the secret combination and the second is how many combinations (potential guesses) we evaluate but do not use as guesses. This paper presents a new search algorithm for mastermind which combines hill climbing and heuristics. It makes a similar number of guesses to the two known genetic algorithm-based methods, but is more efficient in terms of the number of combinations evaluated. It may be applicable to related constraint optimisation problems.

Keywords: mastermind, stochastic search, genetic algorithms, games

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