  In this paper, we study the algorithmic complexity of the Mastermind game,
where results are single-color black pegs. This differs from the usual
dual-color version of the game, but better corresponds to applications in
genetics. We show that it is NP-complete to determine if a sequence of
single-color Mastermind results have a satisfying vector. We also show how to
devise efficient algorithms for discovering a hidden vector through
single-color queries. Indeed, our algorithm improves a previous method of
Chvatal by almost a factor of 2.
