This paper introduces a blazingly fast, no-loss expert system for Tic Tac Toe using Decision Trees called T3DT, that tries to emulate human gameplay as closely as possible. It does not make use of any brute force, minimax or evolutionary techniques, but is still always unbeatable. In order to make the gameplay more human-like, randomization is prioritized and T3DT randomly chooses one of the multiple optimal moves at each step. Since it does not need to analyse the complete game tree at any point, T3DT is exceptionally faster than any brute force or minimax algorithm, this has been shown theoretically as well as empirically from clock-time analyses in this paper. T3DT also doesn't need the data sets or the time to train an evolutionary model, making it a practical no-loss approach to play Tic Tac Toe.

中文翻译：

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随机快速无损专家系统，像人一样玩井字游戏

本文介绍了一种使用称为T3DT的决策树为井字游戏提供了快速，无损的专家系统，该系统试图尽可能模拟人类的游戏玩法。它不使用任何蛮力，极小极大值或进化技术，但始终无与伦比。为了使游戏更具人性化，对随机化进行了优先排序，并且T3DT在每个步骤中随机选择多个最佳移动之一。由于不需要在任何时候分析完整的游戏树，因此T3DT比任何强力算法或minimax算法都快得多，本文从时钟时间分析的理论和经验上都证明了这一点。T3DT还不需要数据集或时间来训练进化模型，因此成为玩Tic Tac Toe的实用无损方法。