计算机象棋程序设计中一种新的走法重复检测方法
A New Approach to Draw Detection by Move Repetition in Computer Chess Programming
摘要：
我们将尝试解决国际象棋编程中一个非常重要的问题的理论和实践方面，正如本文的标题所述-通过移动重复进行平局检测的问题。到目前为止，大多数国际象棋程序中采用的标准方法是基于利用原始和压缩格式的位置矩阵以及所谓的位板格式的实现。我们将尝试引入的新方法是基于在决策树扩展期间使用由搜索算法（search algorithm）生成的变体字符串。我们希望证明这种方法比标准的处理方法更有效，特别是在棋子很少的情况下（残局）。为了说明我们心中的机器语言例程，实现我们的理论假设是附加的。该例程是作者开发的Axon国际象棋程序的一部分。Axon，在其目前的化身，发挥国际象棋大师的力量（约。2400-2450 Elo，基于Axon vs计算机程序和Axon vs人类大师总共超过3000场比赛）。
英文摘要：
We will try to tackle both the theoretical and practical aspects of a very important problem in chess programming as stated in the title of this article - the issue of draw detection by move repetition. The standard approach that has so far been employed in most chess programs is based on utilising positional matrices in original and compressed format as well as on the implementation of the so-called bitboard format. The new approach that we will be trying to introduce is based on using variant strings generated by the search algorithm (searcher) during the tree expansion in decision making. We hope to prove that this approach is more efficient than the standard treatment of the issue, especially in positions with few pieces (endgames). To illustrate what we have in mind a machine language routine that implements our theoretical assumptions is attached. The routine is part of the Axon chess program, developed by the authors. Axon, in its current incarnation, plays chess at master strength (ca. 2400-2450 Elo, based on both Axon vs computer programs and Axon vs human masters in over 3000 games altogether).
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
