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Hands-On Intelligent Agents with OpenAI Gym

You're reading from Hands-On Intelligent Agents with OpenAI Gym

Product type Book

Published in Jul 2018

Publisher Packt

ISBN-13 9781788836579

Pages 254 pages

Edition 1st Edition

Languages

Concepts

Artificial Intelligence

Author (1):

Palanisamy P

Table of Contents (12) Chapters

Preface

1. Introduction to Intelligent Agents and Learning Environments

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

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Creating Custom OpenAI Gym Environments - CARLA Driving Simulator

In the first chapter, we looked at the various categories of learning environments available in the OpenAI Gym environment catalog. We then explored the list of environments and their nomenclature in Chapter 5, Implementing your First Learning Agent – Solving the Mountain Car problem, as well as a sneak peek into some of them. We also developed our agents to solve the Mountain Car and Cart Pole problems, and a few Atari game environments. By now, then, you should have a good understanding of the various environment types and flavors that are available with OpenAI Gym. Most often, once we learn how to develop our own intelligent agents, we want to use that knowledge and skill to develop intelligent agents to solve new problems, problems that we already face, or even problems that are of interest to us. For...

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Authors (1)

Palanisamy P

Praveen Palanisamy works on developing autonomous intelligent systems. He is currently an AI researcher at General Motors R&D. He develops planning and decision-making algorithms and systems that use deep reinforcement learning for autonomous driving. Previously, he was at the Robotics Institute, Carnegie Mellon University, where he worked on autonomous navigation, including perception and AI for mobile robots. He has experience developing complete, autonomous, robotic systems from scratch.

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