谷歌的電腦圍棋程式擊敗了韓國棋王，對人工智慧的發展有很大影響。人工智慧電腦圍棋程式也對圍棋界造成相當大的影響，本篇論文分析從日本棋院幽玄收集到的大量棋譜，這些棋譜包括人機對局棋譜。然後分析電腦圍棋程式對人類下棋造成的影響。由分析結果得知，經常與電腦圍棋程式下棋的人，進步幅度比只有跟人類對手下棋的人高。

The event of AlphaGo defeating human grandmasters made a great impact. We study deep learning and Monte-Carlo tree search to develop a human-like Go-playing computer program by designing different artificial intelligence models to get various difficulties. In this study, we collaborated with a Go platform, called U-gen, to collect hundreds of thousands of data about players for three years. After the analysis of statistical data, we confirmed that those who often play Go against artificial players (computer Go programs) can make substantial progress on improving their Go skills. The more a player uses the platform to play "Go" against our artificial intelligence models rather than playing against humans the more they improve. Moreover, the more a player challenges higher levels of AI opponents, the more improvement the player gains.

Table of Contents
Title Page i
Certificate of Approval of Exam Committee iii
Acknowledgement iv
Abstract (English) v
Abstract (Chinese) vi
Table of Contents vii
List of Tables viii
List of Figures ix
1.Chapter 1: Introduction 1
2.Chapter 2: Learning theory 3
3.Chapter 3: Features of Go Teaching on Website 7
4.Chapter 4: Methods 15
5.Chapter 5: Results 19
6.Chapter 6: Conclusion 29
Acknowledgments 30
References 31

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