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AI Crash Course

You're reading from   AI Crash Course A fun and hands-on introduction to machine learning, reinforcement learning, deep learning, and artificial intelligence with Python

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Product type Paperback
Published in Nov 2019
Publisher Packt
ISBN-13 9781838645359
Length 360 pages
Edition 1st Edition
Languages
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Author (1):
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Hadelin de Ponteves Hadelin de Ponteves
Author Profile Icon Hadelin de Ponteves
Hadelin de Ponteves
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Toc

Table of Contents (17) Chapters Close

Preface 1. Welcome to the Robot World FREE CHAPTER 2. Discover Your AI Toolkit 3. Python Fundamentals – Learn How to Code in Python 4. AI Foundation Techniques 5. Your First AI Model – Beware the Bandits! 6. AI for Sales and Advertising – Sell like the Wolf of AI Street 7. Welcome to Q-Learning 8. AI for Logistics – Robots in a Warehouse 9. Going Pro with Artificial Brains – Deep Q-Learning 10. AI for Autonomous Vehicles – Build a Self-Driving Car 11. AI for Business – Minimize Costs with Deep Q-Learning 12. Deep Convolutional Q-Learning 13. AI for Games – Become the Master at Snake 14. Recap and Conclusion 15. Other Books You May Enjoy 16. Index

Summary

In this chapter we studied the Q-learning model, which is only applied to environments that have a finite number of input states and a finite number of possible actions to perform.

When performing Q-learning, the AI learns Q-values through an iterative process, so that the higher the Q-value of a (state, action) pair, the closer the AI gets to the top reward.

At each iteration the Q-values are updated through the Bellman equation, which simply consists of adding the temporal difference, discounted by a learning rate factor. We will get to work on a full practical Q-learning activity in the next chapter, applied to a real-world business problem.

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