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 contribution | A heuristic hill climbing algorithm for mastermind |
|---|---|
| Original language | English |
| Title of host publication | Unknown |
| Publisher | University of Bristol |
| Pages | 189 - 196 |
| Number of pages | 7 |
| ISBN (Print) | 0862925371 |
| Publication status | Published - Sept 2003 |