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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/98238


    Title: Toward the optimum performance in the Bulls-and-Cows games
    Authors: Liu, Chao-Lin;Chen, Yu-Sheng
    劉昭麟
    Contributors: 資科系
    Date: 2012-11
    Issue Date: 2016-06-22 17:15:18 (UTC+8)
    Abstract: Bulls-and-Cows (BAC) is a popular guessing game worldwide. Players try to find opponents` answers via clues provided by the opponents. Some theoretical analyses indicate that, on average, an optimal strategy takes 5.2131 guesses to find the answers for four-digit games. In this paper, alternative methods were explored to realize this theoretical optimality. The methods include a basic filtering method, different ways to recommend the candidate answers, and a machine-learning based method. The best performing combination of non-deterministic methods identified the correct answers with 5.3135 guesses in 504,000 trials. In addition, we were able to find the answers for five-digit and six-digit BAC games with 5.7800 and 6.3999 guesses.
    Relation: Proceedings of the 2012 Conference on Technologies and Applications of Artificial Intelligence (TAAI`12), 294‒299. Tainan, Taiwan, 16-18 November 2012
    Data Type: conference
    DOI link: http://dx.doi.org/10.1109/TAAI.2012.57
    DOI: 10.1109/TAAI.2012.57
    Appears in Collections:[Department of Computer Science ] Proceedings

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