---
title: "Chess_db：用于处理大型国际象棋游戏数据集的逻辑编程框架"
source: "arXiv AI/CL/LG（论文）"
source_tier: "t2"
url: "https://arxiv.org/abs/2607.21195v1"
permalink: "https://feed.astralor.com/items/itm_56b8b9f274682a9cd6227ff6"
published: "2026-07-23T11:17:41.000Z"
score: 74
channel: "tech"
tags: ["Chess_db","LMDB","PGN","国际象棋","逻辑编程","键值存储"]
---

# Chess_db：用于处理大型国际象棋游戏数据集的逻辑编程框架

## AI 点评

> 这篇论文虽然聚焦于棋类，但其‘逻辑编程+键值存储’处理大规模结构化数据的思路值得AI从业者借鉴。如果你在构建需要快速查询大量历史数据（如棋谱、运动轨迹、时序事件）的系统，Chess_db的设计模式可以迁移。论文本身代码质量不错，推荐给对数据密集型AI应用或棋类AI有兴趣的工程师。

## 速览

Chess_db 是一个逻辑编程工具套件，旨在高效处理大规模国际象棋游戏数据集。它支持从 PGN 文件创建数据库，并利用开源键值存储实现近乎即时的局面信息查询，涵盖特定棋手的历史对局和局面胜负统计。该工作挑战了“引擎超越人类会削弱棋类兴趣”的假设，转而关注如何用计算资源辅助棋手训练。实验表明，该框架能处理数百万局游戏并快速检索关键统计信息，对棋类分析和 AI 研究均有实用价值。

## 关键点

- 提出 Chess_db 框架，使用逻辑编程（如 Prolog）处理棋盘局面和游戏数据。
- 支持从 PGN 文件创建数据库，并利用开源键值存储（如 LMDB）实现快速局面查询。
- 可查询特定棋手的对局历史及特定局面下白方/黑方的胜率统计。
- 开源实现，适用于棋类训练、AI 引擎数据分析等场景。

## 全文

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.

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