Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Reinforcement Learning with TensorFlow

You're reading from   Reinforcement Learning with TensorFlow A beginner's guide to designing self-learning systems with TensorFlow and OpenAI Gym

Arrow left icon
Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788835725
Length 334 pages
Edition 1st Edition
Languages
Arrow right icon
Author (1):
Arrow left icon
Sayon Dutta Sayon Dutta
Author Profile Icon Sayon Dutta
Sayon Dutta
Arrow right icon
View More author details
Toc

Table of Contents (17) Chapters Close

Preface 1. Deep Learning – Architectures and Frameworks 2. Training Reinforcement Learning Agents Using OpenAI Gym FREE CHAPTER 3. Markov Decision Process 4. Policy Gradients 5. Q-Learning and Deep Q-Networks 6. Asynchronous Methods 7. Robo Everything – Real Strategy Gaming 8. AlphaGo – Reinforcement Learning at Its Best 9. Reinforcement Learning in Autonomous Driving 10. Financial Portfolio Management 11. Reinforcement Learning in Robotics 12. Deep Reinforcement Learning in Ad Tech 13. Reinforcement Learning in Image Processing 14. Deep Reinforcement Learning in NLP 15. Further topics in Reinforcement Learning 16. Other Books You May Enjoy

Why reinforcement learning?


In 2014, Google acquired a London-based startup named DeepMind for a whopping $500 million. In the news, we read that they had created an AI agent to beat any Atari game, but the main reason why Google paid so much to acquire it was because this breakthrough was a step closer toward general artificial intelligence. General artificial intelligence is referred to as an AI agent. It is capable of doing a variety of tasks and generalizing just like a human. When it surpasses that, that point of singularity is termed, artificial super intelligence. At present, the work done by the AI community is what we term, artificial narrow intelligence, where an AI agent is capable of acing a couple of tasks but not able to generalize over a variety of tasks. 

DeepMind published their paper, Human Level Control through Deep Reinforcement Learning in the research journal Nature ( http://www.davidqiu.com:8888/research/nature14236.pdf) showing that their deep reinforcement learning...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime