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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

Implementing your First Learning Agent - Solving the Mountain Car problem

Well done on making it this far! In previous chapters, we got a good introduction to OpenAI Gym, its features, and how to install, configure, and use it in your own programs. We also discussed the basics of reinforcement learning and what deep reinforcement learning is, and we set up the PyTorch deep learning library to develop deep reinforcement learning applications. In this chapter, you will start developing your first learning agent! You will develop an intelligent agent that will learn how to solve the Mountain Car problem. Gradually in the following chapters, we will solve increasingly challenging problems as you get more comfortable developing reinforcement learning algorithms to solve problems in OpenAI Gym. We will start this chapter by understanding the Mountain Car problem, which has been a popular...

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