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，像人类一样玩井字游戏

本文介绍了一个使用决策树的 Tic Tac Toe 的极速、无损失的专家系统，称为 T3DT，它试图尽可能地模拟人类游戏玩法。它没有使用任何蛮力、极小极大或进化技术，但仍然始终是无与伦比的。为了使游戏玩法更人性化，随机化被优先考虑，T3DT 在每一步随机选择多个最佳动作之一。由于它不需要在任何时候分析完整的博弈树，T3DT 比任何蛮力算法或极小极大算法都快得多，这在本文的时钟时间分析中已经从理论上和经验上得到了证明。T3DT 也不需要数据集或时间来训练进化模型，使其成为玩 Tic Tac Toe 的实用无损失方法。