论文标题
AI驱动的机制作为法官：在国际象棋中打破联系
AI-powered mechanisms as judges: Breaking ties in chess
论文作者
论文摘要
最近，人工智能（AI）的技术使用在体育运动中一直在增加，以达到各种复杂性的决策。例如，在相对较低的复杂性水平上，主要的网球比赛用Hawk-eye Live技术取代了人类线的法官，以减少19日大流行期间的员工。但是，AI现在准备超越此类平凡的任务。一个很好的例子和完美的应用程序是国际象棋。为了减少联系的日益增长的发病率，许多精英锦标赛都诉诸于迅速的国际象棋打决赛。但是，这些决胜局大大降低了游戏的质量。为了解决这个问题，我们提出了一种新型的AI驱动方法，以实现客观的打扣机制。这种方法通过将玩家移动的质量与强大的国际象棋发动机建议的最佳动作进行比较来评估玩家的动作质量。如果有领带，具有较高质量的球员将赢得抢七局。这种方法不仅增强了比赛的公平性和完整性，而且还保持了游戏的高标准。为了显示我们的方法的有效性，我们将其应用于一个数据集，其中包括从1910年到2018年的世界国际象棋冠军赛大约25,000个大师进行，使用了主要的国际象棋AI，用于分析。
Recently, Artificial Intelligence (AI) technology use has been rising in sports to reach decisions of various complexity. At a relatively low complexity level, for example, major tennis tournaments replaced human line judges with Hawk-Eye Live technology to reduce staff during the COVID-19 pandemic. AI is now ready to move beyond such mundane tasks, however. A case in point and a perfect application ground is chess. To reduce the growing incidence of ties, many elite tournaments have resorted to fast chess tiebreakers. However, these tiebreakers significantly reduce the quality of games. To address this issue, we propose a novel AI-driven method for an objective tiebreaking mechanism. This method evaluates the quality of players' moves by comparing them to the optimal moves suggested by powerful chess engines. If there is a tie, the player with the higher quality measure wins the tiebreak. This approach not only enhances the fairness and integrity of the competition but also maintains the game's high standards. To show the effectiveness of our method, we apply it to a dataset comprising approximately 25,000 grandmaster moves from World Chess Championship matches spanning from 1910 to 2018, using Stockfish 16, a leading chess AI, for analysis.
