神经连接4 -一个连接的方法来游戏

M. Schneider, J. Rosa
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引用次数: 18

摘要

本文介绍了一个名为“Neural Connect 4”的系统,它是一个玩“Connect 4”游戏的程序。该系统采用多层感知器结构,通过监督反向传播算法进行学习。训练所需的知识来自于保存的游戏。在对游戏本身进行简短介绍之后,描述了用于训练和评估的符号算法。在连接主义方法中进行比较:显示有效和无效的学习技术,并讨论了结果。“神经连接4”证明了人工神经网络在遵循一定原则的情况下完全可以用来学习“神经连接4”。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Neural Connect 4 - a connectionist approach to the game
This article presents the system "Neural Connect 4", a program that plays the game Connect Four. This system employs the multilayer perceptron architecture which learns through the supervised backpropagation algorithm. The required knowledge for training comes from saved games. After a short introduction to the game itself, the symbolic algorithms used for training and evaluation are described. Comparisons are made within a connectionist approach: effective and ineffective learning techniques are shown, and the results are discussed. "Neural Connect 4" proves that artificial neural networks are completely adequate for learning Connect Four, given that certain principles are observed.
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