A heuristic hill climbing algorithm for mastermind

A Temporel, T Kovacs

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

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
Translated title of the contributionA heuristic hill climbing algorithm for mastermind
Original languageEnglish
Title of host publicationUnknown
PublisherUniversity of Bristol
Pages189 - 196
Number of pages7
ISBN (Print)0862925371
Publication statusPublished - Sep 2003

Bibliographical note

Conference Proceedings/Title of Journal: Proceedings of the 2003 UK Workshop on Computational Intelligence (UKCI-03)

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