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Optimal Analyses for 3×n AB Games in the Worst Case

  • Li-Te Huang
  • Shun-Shii Lin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6048)

Abstract

The past decades have witnessed a growing interest in research on deductive games such as Mastermind and AB game. Because of the complicated behavior of deductive games, tree-search approaches are often adopted to find their optimal strategies. In this paper, a generalized version of deductive games, called 3×n AB games, is introduced. However, traditional tree-search approaches are not appropriate for solving this problem since it can only solve instances with smaller n. For larger values of n, a systematic approach is necessary. Therefore, intensive analyses of playing 3×n AB games in the worst case optimally are conducted and a sophisticated method, called structural reduction, which aims at explaining the worst situation in this game is developed in the study. Furthermore, a worthwhile formula for calculating the optimal numbers of guesses required for arbitrary values of n is derived and proven to be final.

Keywords

Mastermind Strategy Optimal Analysis Hard State Apply Soft Computing Adversary Response 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Li-Te Huang
    • 1
  • Shun-Shii Lin
    • 1
  1. 1.Department of Computer Science and Information EngineeringNational Taiwan Normal UniversityTaipeiTaiwan, ROC

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