An efficient approach to solve mastermind optimally

Li Te Huang, Shan Tai Chen, Shih Chieh Huang, Shun Shii Lin

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

The Mastermind game is well-known around the world. In recent decades, several approaches have been adopted for solving Mastermind in the worst case. An optimal strategy has finally been proposed by Koyoma and Lai in 1993 by using an exhaustive search for finding the optimal strategy in the expected case. In this paper, a more efficient backtracking algorithm with branch-and-bound pruning (BABBP) for Mastermind in the expected case is introduced, and an alternative optimal strategy is obtained eventually. Furthermore, the novel approach may be presumably applied to other games with some modifications in order to speed up the search.

Original languageEnglish
Pages (from-to)143-149
Number of pages7
JournalICGA Journal
Volume30
Issue number3
DOIs
Publication statusPublished - 2007 Sep

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Computational Mechanics
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design

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