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Keras Reinforcement Learning Projects

You're reading from   Keras Reinforcement Learning Projects 9 projects exploring popular reinforcement learning techniques to build self-learning agents

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Product type Paperback
Published in Sep 2018
Publisher Packt
ISBN-13 9781789342093
Length 288 pages
Edition 1st Edition
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Author (1):
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Giuseppe Ciaburro Giuseppe Ciaburro
Author Profile Icon Giuseppe Ciaburro
Giuseppe Ciaburro
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Table of Contents (13) Chapters Close

Preface 1. Overview of Keras Reinforcement Learning FREE CHAPTER 2. Simulating Random Walks 3. Optimal Portfolio Selection 4. Forecasting Stock Market Prices 5. Delivery Vehicle Routing Application 6. Continuous Balancing of a Rotating Mechanical System 7. Dynamic Modeling of a Segway as an Inverted Pendulum System 8. Robot Control System Using Deep Reinforcement Learning 9. Handwritten Digit Recognizer 10. Playing the Board Game Go 11. What's Next? 12. Other Books You May Enjoy

Summary

In this chapter, you learned the general concepts of game theory. Game theory is the mathematical science that studies and analyzes the individual decisions of a subject in situations of conflict or strategic interaction with other rival subjects aimed at the maximum profit of each subject. Game theory's main objective is the victory; everyone must be aware of the rules of the game, and be aware of the consequences of every single move. The set of moves that an individual intends to perform is called a strategy. We have analyzed the different types of games predicted by the theory and various practical applications in real time: the prisoner's dilemma, stag hunt, and chicken game.

Then we explored the AlphaGo DeepMind project. Go is a strategic board game for two players. AlphaGo is a software for the game of Go developed by Google DeepMind. It was the first...

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