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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

Simulating Random Walks

Stochastic processes involve systems that evolve over time (but also more generally in space) according to probabilistic laws. Such systems or models describe the complex phenomena of the real world that have the possibility of being random. These phenomena are more frequent than we can believe. We encounter these phenomena when the quantities we are interested in are not predictable with absolute certainty. However, when such phenomena show a variability of possible outcomes that can be somehow explained or described, then we can introduce a probabilistic model of the phenomenon.

For example, say that we are examining the motion involved in a random walking movement. We study the motion of an object that is constrained to move along a straight line in the two directions allowed. At each movement, it moves randomly to the right or left, each step being...

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