Liu M. AlphaGo Simplified.Rule-Based AI and Deep Learning in Everyday Games 2025

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Liu M. AlphaGo Simplified.Rule-Based AI and Deep Learning in Everyday Games 2025

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Textbook in PDF format May 11, 1997, was a watershed moment in the history of artificial intelligence (AI): the IBM supercomputer chess engine, Deep Blue, beat the world Chess champion, Garry Kasparov. It was the first time a machine had triumphed over a human player in a Chess tournament. Fast forward 19 years to May 9, 2016, DeepMind’s AlphaGo beat the world Go champion Lee Sedol. AI again stole the spotlight and generated a media frenzy. This time, a new type of AI algorithm, namely machine learning (ML) was the driving force behind the game strategies. What exactly is ML? How is it related to AI? Why is deep learning (DL) so popular these days? This book explains how traditional rule-based AI and ML work and how they can be imple mented in everyday games such as Last Coin Standing, Tic Tac Toe, or Connect Four. Game rules in these three games are easy to implement. As a result, readers will learn rule-based AI, deep reinforcement learning, and more importantly, how to combine the two to create powerful game strategies (the whole is indeed greater than the sum of its parts) without getting bogged down in complicated game rules. Preface Section I Rule-Based AI Rule-Based AI in the Coin Game Look-Ahead Search in Tic Tac Toe Planning Three Steps Ahead in Connect Four Recursion and MiniMax Tree Search Depth Pruning in MiniMax Alpha-Beta Pruning Position Evaluation in MiniMax Monte Carlo Tree Search Section II Deep Learning Deep Learning in the Coin Game Policy Networks in Tic Tac Toe A Policy Network in Connect Four Section III Reinforcement Learning Tabular Q-Learning in the Coin Game Self-Play Deep Reinforcement Learning Vectorization to Speed Up Deep Reinforcement Learning A Value Network in Connect Four Section IV AlphaGo Algorithms Implementing AlphaGo in the Coin Game AlphaGo in Tic Tac Toe and Connect Four Hyperparameter Tuning in AlphaGo The Actor-Critic Method and AlphaZero Iterative Self-Play and AlphaZero in Tic Tac Toe AlphaZero in Unsolved Games Bibliography