基于遗传算法的终局数据库模式挖掘

Heriniaina Andry Raboanary, J. Raboanary, T. Raboanary
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引用次数: 0

摘要

“井字棋”和“法诺罗纳”游戏是可以通过计算机引擎在极高水平上玩的游戏。Endgame数据库是创建这些引擎的强大工具。这些终局数据库包含了关于如何玩游戏的宝贵信息。不幸的是,人类玩家几乎不可能从终局数据库中学习游戏策略,因为终局数据库只是由原始的比特序列组成的。这里介绍的工作是使用遗传算法从这些数据库中提取对人类友好的知识。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using a Genetic Algorithm for Mining Patterns from Endgame Databases
Tic-tac-toe and Fanorona games are ones that can be played at an extremely high level by computer engines. Endgame databases are powerful tools to create these engines. These Endgame databases contain precious information's about how to play the game. Unfortunately, it is quite impossible for human players to learn the game strategies from endgame databases, which are only made of raw sequences of bits. The work presented here is the use of genetic algorithms to extract human friendly knowledge from these databases.
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