比较粒子群结构从零知识学习跳棋游戏

The 2003 Congress on Evolutionary Computation, 2003. CEC '03. Pub Date : 2003-12-08 DOI:10.1109/CEC.2003.1299580

N. Franken, A. Engelbrecht

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引用次数: 53

摘要

本文研究了各种粒子群优化器结构在学习如何玩跳棋游戏中的有效性。共同进化技术用于训练游戏代理。将玩家的表现与随机移动进行比较。初步的实验结果表明，使用一定的信息共享结构和群体大小配置来成功学习跳棋游戏具有一定的优势。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Comparing PSO structures to learn the game of checkers from zero knowledge

This paper investigates the effectiveness of various particle swarm optimiser structures to learn how to play the game of checkers. Co-evolutionary techniques are used to train the game playing agents. Performance is compared against a player making moves at random. Initial experimental results indicate definite advantages in using certain information sharing structures and swarm size configurations to successfully learn the game of checkers.

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The 2003 Congress on Evolutionary Computation, 2003. CEC '03.

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