发表机构
University College \& Imperial College
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究围绕国际象棋游戏数据集展开，提出Chess_db框架，它是一套逻辑编程工具，能有效处理棋局，可从PGN文件创建数据库并探讨开源键值数据库适用性，为处理大型国际象棋游戏数据集提供了有效方法。
AI 中文摘要
国际象棋是一款双人策略游戏，曾是智能行为的前沿领域，深植于经典人工智能文化之中。曾有人暗自认为，比顶尖人类棋手更强的计算机引擎出现后，人们会对国际象棋失去兴趣。然而事实恰恰相反，国际象棋的追随者日益增多。当前大量计算资源集中在棋手训练上，引擎输出只是其中一方面。获取过往棋局同样至关重要，既能了解特定棋手之前的对局，也能知晓特定局面下每种颜色棋手哪种后续走法更易获胜。我们展示了Chess_db，这是一套逻辑编程工具，能在内存中及通过创建后端数据库有效处理棋局。特别是，我们提供了从PGN（便携式棋局记法）游戏文件创建数据库的通用代码，并探讨了开源键值数据库存储局面表的适用性，这些局面表能近乎即时获取大量棋局相关信息。
英文摘要
Chess is a two player strategic game that is embedded in classical AI culture as it was once the frontier for intelligent behaviour. There was the silent assumption that the advent of computer engines that play better than the best humans will extinguish interest in the game. However, the opposite has come to pass, with a growing following for the game. A lot of the computational resources are now centered around training of players, where the engine output is just one aspect. Access to past games is also an essential part, both in knowing what games a specific player has played previously, and also which continuations at a certain position have led to victory more often for each of the two colour players. We present Chess_db a suite of logic programming tools that can effectively manipulate games both in memory and via creating back end databases. In particular, we provide versatile code that creates databases from PGN (portable game notation) game files and explore the suitability of open source key-value databases for storing position tables that provide near-instant access to information pertaining to substantially large number of games.
CommentsIn Proceedings ICLP 2026, arXiv:2607.17707
Journal refEPTCS 450, 2026, pp. 196-208
