Evolutionary Learning for Playing a Gobang Game

• Main Authors: Bing-Wen Chuang, 莊秉文
• Other Authors: Yi-Tsung Yjuan
• Format: Others
• Language: zh-TW
• Published: 2003
• Online Access: http://ndltd.ncl.edu.tw/handle/vmd3d5

碩士 === 中原大學 === 資訊工程研究所 === 91 === In this paper, we will discuss with using Genetic Algorithm (GA) on producing a strategy for playing a Gobang game, the original random strategy at the beginning of the first generation is hard to win an opponent, but after the evoulationary process, the strategy of GA will become more intelligent. The purpose of this paper is designing a evolutionary model for GA, it let GA efficiently and quickly obtain the result which conforms to us.We proposed two different models to find the same solution or purpose, due to different models make the diversity of them in efficient and speed.The first model is designed with a general decision tree ,is not good enough for learning strategy, but the second one is suitable for learning and contains two new correcting methods, it speed up the learning ability in evolutionary process.I show in this paper that how the flow path of evolutionary learning algorithm will be driven.