کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
482319 | 1446187 | 2007 | 10 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Strategy optimization for deductive games Strategy optimization for deductive games](/preview/png/482319.png)
This paper presents novel algorithms for strategy optimization for deductive games. First, a k-way-branching (KWB) algorithm, taking advantage of a clustering technique, can obtain approximate results effectively. Second, a computer-aided verification algorithm, called the Pigeonhole-principle-based backtracking (PPBB) algorithm, is developed to discover the lower bound of the number of guesses required for the games. These algorithms have been successfully applied to deductive games, Mastermind and “Bulls and Cows.” Experimental results show that KWB outperforms previously published approximate strategies. Furthermore, by applying the algorithms, we derive the theorem: 7 guesses are necessary and sufficient for the “Bulls and Cows” in the worst case. These results suggest strategies for other search problems.
Journal: European Journal of Operational Research - Volume 183, Issue 2, 1 December 2007, Pages 757–766