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Hands-On Intelligent Agents with OpenAI Gym

You're reading from   Hands-On Intelligent Agents with OpenAI Gym Your guide to developing AI agents using deep reinforcement learning

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Product type Paperback
Published in Jul 2018
Publisher Packt
ISBN-13 9781788836579
Length 254 pages
Edition 1st Edition
Languages
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Author (1):
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Palanisamy Palanisamy
Author Profile Icon Palanisamy
Palanisamy
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Table of Contents (12) Chapters Close

Preface 1. Introduction to Intelligent Agents and Learning Environments FREE CHAPTER 2. Reinforcement Learning and Deep Reinforcement Learning 3. Getting Started with OpenAI Gym and Deep Reinforcement Learning 4. Exploring the Gym and its Features 5. Implementing your First Learning Agent - Solving the Mountain Car problem 6. Implementing an Intelligent Agent for Optimal Control using Deep Q-Learning 7. Creating Custom OpenAI Gym Environments - CARLA Driving Simulator 8. Implementing an Intelligent - Autonomous Car Driving Agent using Deep Actor-Critic Algorithm 9. Exploring the Learning Environment Landscape - Roboschool, Gym-Retro, StarCraft-II, DeepMindLab 10. Exploring the Learning Algorithm Landscape - DDPG (Actor-Critic), PPO (Policy-Gradient), Rainbow (Value-Based) 11. Other Books You May Enjoy

Understanding what AI means and what's in it in an intuitive way

The intelligence demonstrated by humans and animals is called natural intelligence, but the intelligence demonstrated by machines is called AI, for obvious reasons. We humans develop algorithms and technologies that provide intelligence to machines. Some of the greatest developments on this front are in the fields of machine learning, artificial neural networks, and deep learning. These fields collectively drive the development of AI. There are three main types of machine learning paradigms that have been developed to some reasonable level of maturity so far, and they are the following:

  • Supervised learning
  • Unsupervised learning
  • Reinforcement learning

In the following diagram, you can get an intuitive picture of the field of AI. You can see that these learning paradigms are subsets of the field of machine learning...

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