Valuation of Convolutional Neural Network in Intelligent Computer Games

被引：0
|
作者：
Wu, Gui [1 ]
Zeng, Peng [2 ]
机构：
[1] Jianghan Univ, Educ Adm Off, Wuhan, Peoples R China
[2] Jianghan Univ, Sch Artificial Intelligence, Wuhan, Peoples R China
来源：
2023 35TH CHINESE CONTROL AND DECISION CONFERENCE, CCDC | 2023年
关键词：
Convolution Neural Network; Evaluation Algorithm; Incomplete Information Games; Texas Games;
D O I：
10.1109/CCDC58219.2023.10326857
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Many problems in incomplete information games also exist in our daily life. It is of great significance to solve the problems in our daily life and improve the quality. Texas Holdem is a typical card game with incomplete information. For Texas Holdem a valuation algorithm model based on convolutional neural network is proposed. To train the model using the game history between the masters, to achieve the purpose of learning master skill. The game procedure of the valuation model plays the game with the game procedure designed by the predecessors, and the experimental results show that the convolutional neural network valuation method of learning human master experience can provide better decisions and enhance the Texas Holdem game procedure.
引用
收藏
页码：2303 / 2307
页数：5
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