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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

Solving the knapsack problem using Dynamic Programming

We introduced DP in the previous sections. Now the time has come to tackle a practical case. We will do this by analyzing a classic problem that has been studied for more than a century since 1897: the knapsack problem. The first to deal with it was the mathematician Tobias Dantzig, who based the name on the common problem of packing the most useful items in a knapsack without overloading it.

A problem of this type can be associated with different situations arising from real life. To better characterize the problem, we will propose another, rather unique problem. A thief goes into a house and wants to steal valuables. They put them in their knapsack, but they are limited by the weight. Each object has its own value and weight. He must choose the objects that are of value, but that do not have excessive weight. The thief must...

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