Implementing a no-loss state in the game of Tic-Tac-Toe using a customized Decision Tree Algorithm

S. Sriram, R. Vijayarangan, Saaisree Raghuraman, Xiaobu Yuan
{"title":"Implementing a no-loss state in the game of Tic-Tac-Toe using a customized Decision Tree Algorithm","authors":"S. Sriram, R. Vijayarangan, Saaisree Raghuraman, Xiaobu Yuan","doi":"10.1109/ICINFA.2009.5205101","DOIUrl":null,"url":null,"abstract":"The game of Tic-Tac-Toe is one of the most commonly known games. This game doesn't allow one to win all the time and a significant proportion of games played results in a draw. This study is aimed at evolving of no-loss strategies in the game using Decision Tree Algorithm and comparing them with existing methodologies, mainly focused on the implementation of the game using the Minimax algorithm. The Minimax algorithm does provide an optimal No-Loss Strategy by assuming that both players play optimally. So the question that comes out is what happens when the opponent plays un-optimally, in these cases the minimax proved to play non optimal moves, even though it wins at the next state rather than the expected state. Thus this paper provides a clear study of those trivial states and provides an optimal game play using an decision tree algorithm independent of the opponent's game strategy.","PeriodicalId":223425,"journal":{"name":"2009 International Conference on Information and Automation","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Information and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICINFA.2009.5205101","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

Abstract

The game of Tic-Tac-Toe is one of the most commonly known games. This game doesn't allow one to win all the time and a significant proportion of games played results in a draw. This study is aimed at evolving of no-loss strategies in the game using Decision Tree Algorithm and comparing them with existing methodologies, mainly focused on the implementation of the game using the Minimax algorithm. The Minimax algorithm does provide an optimal No-Loss Strategy by assuming that both players play optimally. So the question that comes out is what happens when the opponent plays un-optimally, in these cases the minimax proved to play non optimal moves, even though it wins at the next state rather than the expected state. Thus this paper provides a clear study of those trivial states and provides an optimal game play using an decision tree algorithm independent of the opponent's game strategy.
使用自定义决策树算法实现一字棋游戏中的无损失状态
井字游戏是最广为人知的游戏之一。这个游戏不允许一个人一直获胜,而且相当一部分比赛结果是平局。本研究旨在利用决策树算法在博弈中发展无损失策略,并将其与现有方法进行比较,主要关注使用极小极大算法实现博弈。极大极小算法确实提供了一个最优的无损失策略,假设双方都是最优的。那么问题来了,当对手采取非最优棋法时,在这种情况下,极大极小被证明采取了非最优棋法,即使它在下一个状态而不是预期状态下获胜。因此,本文提供了对这些琐碎状态的清晰研究,并使用独立于对手博弈策略的决策树算法提供了最优博弈。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信