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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
Author (1):
Palanisamy P Palanisamy P
Profile icon Palanisamy P
LinkedIn
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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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

What is reinforcement learning?

If you are new to the field of Artificial Intelligence (AI) or machine learning, you might be wondering what reinforcement learning is all about. In simple terms, it is learning through reinforcement. Reinforcement, as you know from general English or psychology, is the act of increasing or strengthening the choice to take a particular action in response to something, because of the perceived benefit of receiving higher rewards for taking that action. We humans are good at learning through reinforcement from a very young age. Those who have kids may be utilizing this fact more often to teach good habits to them. Nevertheless, we will all be able to relate to this, because not so long ago we all went through that phase of life! Say parents reward their kid with chocolate if the kid completes their homework on time after school every day. The kid...

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Authors (1)

Profile icon Palanisamy P
LinkedIn
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.
See other products by Palanisamy P

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