

#25299
Mentioned in 2 episodes
AlphaGo Simplified
Rule-Based AI and Deep Learning in Everyday Games
Book • 2015
This book explains how traditional rule-based AI and modern machine learning techniques, such as deep reinforcement learning, can be combined to create powerful game strategies in everyday games like Tic Tac Toe, Connect Four, and Last Coin Standing.
Written for both general readers and industry professionals, it covers foundational algorithms like MiniMax, alpha-beta pruning, and Monte Carlo Tree Search, and demonstrates how to integrate them with neural networks and reinforcement learning.
The book is designed to be accessible, with clear explanations and practical examples that do not require advanced computing resources.
Written for both general readers and industry professionals, it covers foundational algorithms like MiniMax, alpha-beta pruning, and Monte Carlo Tree Search, and demonstrates how to integrate them with neural networks and reinforcement learning.
The book is designed to be accessible, with clear explanations and practical examples that do not require advanced computing resources.
Mentioned by
Mentioned in 2 episodes
Mentioned by 

to explain that the algorithms behind it are not decision trees.


Daniel Mahr

15 snips
Daniel Mahr – Glass Box Quant at MDT Advisers (EP.472)
Mentioned by 

in the context of AI's potential to surpass human limitations in trading strategies.


Josh Kale

DeepSeek Traded Its Way To A 2x. Can You Do It Yourself?




