Deep Learning and the Game of Go (pdf)

Description

Table of Contents

PART 1 – FOUNDATIONS

1. 1. Toward deep learning: a machine-learning introduction
   2. Go as a machine-learning problem
   3. Implementing your first Go bot

PART 2 – MACHINE LEARNING AND GAME AI

1. 1. Playing games with tree search
   2. Getting started with neural networks
   3. Designing a neural network for Go data
   4. Learning from data: a deep-learning bot
   5. Deploying bots in the wild
   6. Learning by practice: reinforcement learning
   7. Reinforcement learning with policy gradients
   8. Reinforcement learning with value methods
   9. Reinforcement learning with actor-critic methods

PART 3 – GREATER THAN THE SUM OF ITS PARTS

1. AlphaGo: Bringing it all together
2. AlphaGo Zero: Integrating tree search with reinforcement learning

About the Technology

The ancient strategy game of Go is an incredible case study for AI. In 2016, a deep learning-based system shocked the Go world by defeating a world champion. Shortly after that, the upgraded AlphaGo Zero crushed the original bot by using deep reinforcement learning to master the game. Now, you can learn those same deep learning techniques by building your own Go bot!Summary

Deep Learning and the Game of Go teaches you how to apply the power of deep learning to complex reasoning tasks by building a Go-playing AI. After exposing you to the foundations of machine and deep learning, you’ll use Python to build a bot and then teach it the rules of the game.

Foreword by Thore Graepel, DeepMind

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.What’s inside

• Build and teach a self-improving game AI
• Enhance classical game AI systems with deep learning
• Implement neural networks for deep learning

About the Reader

All you need are basic Python skills and high school-level math. No deep learning experience required.

About the Author

Max Pumperla and Kevin Ferguson are experienced deep learning specialists skilled in distributed systems and data science. Together, Max and Kevin built the open source bot BetaGo.