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Artificial Intelligence with Python Cookbook

You're reading from   Artificial Intelligence with Python Cookbook Proven recipes for applying AI algorithms and deep learning techniques using TensorFlow 2.x and PyTorch 1.6

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Product type Paperback
Published in Oct 2020
Publisher Packt
ISBN-13 9781789133967
Length 468 pages
Edition 1st Edition
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Authors (2):
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Ritesh Kumar Ritesh Kumar
Author Profile Icon Ritesh Kumar
Ritesh Kumar
Ben Auffarth Ben Auffarth
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Ben Auffarth
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Table of Contents (13) Chapters Close

Preface 1. Getting Started with Artificial Intelligence in Python 2. Advanced Topics in Supervised Machine Learning FREE CHAPTER 3. Patterns, Outliers, and Recommendations 4. Probabilistic Modeling 5. Heuristic Search Techniques and Logical Inference 6. Deep Reinforcement Learning 7. Advanced Image Applications 8. Working with Moving Images 9. Deep Learning in Audio and Speech 10. Natural Language Processing 11. Artificial Intelligence in Production 12. Other Books You May Enjoy

Writing a chess engine with Monte Carlo tree search

Chess is a two-player board game that's been popular as a game of wits since the 15th century. A computer beat the first human player in the 1950s (a complete novice) before one beat the human world champion in 1997. They have since moved on to having superhuman intelligence. One of the main difficulties of writing a chess engine a computer program that plays chess is searching through the many variations and combinations and picking the best one.

In this recipe, we'll use Monte Carlo tree search to create a basic chess engine.

Getting ready

We'll use the python-chess library for visualization, to get valid moves, and to know if a state is terminal. We can install it with the pip command, as follows:

pip install python-chess

We'll be using this library for visualization, to generate valid moves at each position, and to check if we've reached a final position.

How to do it...

This recipe is based...

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