计算机与现代化

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俄罗斯方块的Hamming神经网络模型

  

  1. (1.广东科学技术职业学院计算机工程技术学院,广东广州510640;2.广东工业大学环境科学与工程学院,广东广州510006)
  • 收稿日期:2019-05-05 出版日期:2020-03-03 发布日期:2020-03-03
  • 作者简介:刘昌平(1975-),男,湖南祁阳人,讲师,博士,研究方向:人工智能,信息安全,E-mail: goodlcp@163.com; 刘海(1974-),男,江西泰和人,副教授,硕士,研究方向:图像处理,人工智能,语义识别,E-mail: 282474395@qq.com; 夏梦(1984-),女,山东高密人,讲师,硕士,研究方向:用户体验,人工智能,E-mail: 281423727@qq.com; 尹光彩(1973-),女,湖南石门人,副教授,博士,研究方向:数值计算,地理信息系统,E-mail: gcyin@163.com。
  • 基金资助:
    国家重点研发计划项目(2018YFC1800304); 广州市科技计划项目(2016201604030017)

Hamming Neural Network Model for Tetris Game

  1. (1. Computer Engineering Technical College, Guangdong Polytechnic of Science and Technology, Guangzhou 510640, China; 
    2. School of Environmental Science and Engineering, Guangdong University of Technology, Guangzhou 510006, China)
  • Received:2019-05-05 Online:2020-03-03 Published:2020-03-03

摘要: 人工智能技术在游戏的应用非常广泛。提出一种基于Hamming神经网络的俄罗斯方块游戏模型,该模型首先利用局势图不同位置上的方块构成一个模式矩阵,将下落的方块视为待匹配的模式,在Hamming网络的前馈层进行模式匹配,计算出模式间Hamming距离,在递归层进行迭代寻优,得到方块的最佳位置与姿态。在MATLAB上实现了该模型及其游戏,能够自动堆积俄罗斯方块。与已有的评估函数及算法相比,该模型更具有一般性,可为其他类型游戏的建模提供参考。

关键词: 人工智能, 神经网络, 游戏, 模式识别

Abstract: Artificial intelligence has been widely applied to computer games. A hamming neural network games model was proposed for Tetris game. In this model, a pattern matrix was created according to blocks of different position on a given blocks map. 〖JP3〗The falling block acted as a waiting match block. Pattern match was performed in the feedforward layer of hamming neural network to obtain the hamming distance among patterns. The optimistic position and shape were achieved in the recursive layer of hamming neural network. This module and its game were realized using MATLAB to cumulate automatically blocks. Compared with other evaluation function and algorithms, this model has its own generic characters and can be adapted to modeling of other computer games.

Key words: artificial intelligence, neural network, game, pattern recognition

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