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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

Random walks

Random walks are a mathematical model that is used to describe a path that is given by a succession of random steps, which, depending on the system that we want to describe, may have a certain number of degrees of freedom or direction. The term random walk was introduced by Karl Pearson in 1905. In a random walk, each step has a random direction and possibly also a random dimension. It represents a theoretical model to describe any random process through the evolution of known quantities that follow a precise statistical distribution. Physically speaking, the path that we are going to draw over time will not necessarily describe a real motion, but rather indicate more generally the evolution of features over time. This means that random walks find applications in physics, chemistry, and biology, but also in other fields, such as computer science, economics, and sociology...

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