Near-Optimal Strategies for Variations of the Mastermind Game.

Many efficient algorithms, or strategies, have been proposed to solve the Mastermind game that try to minimize the expected number of guesses in order to acquire the secret code. An optimal strategy was found by Koyoma and Lai [6] that uses a depth first search approach. It is very time consuming since it explores every possible combination for every possible guess at each step. Some greedy algorithms have also been proposed that run much faster that explore the next best guess trying every possible combination but only looking one step ahead. These algorithms are considered in this paper to compare how they perform for different versions of the game. Computational results are provided to compare the effectiveness of these strategies for the versions of the game considered. [ABSTRACT FROM AUTHOR]