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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
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Palanisamy
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Table of Contents (12) Chapters Close

Preface 1. Introduction to Intelligent Agents and Learning Environments 2. Reinforcement Learning and Deep Reinforcement Learning FREE CHAPTER 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

Creating an OpenAI Gym-compatible CARLA driving simulator environment

CARLA is a driving simulator environment built on top of the UnrealEngine4 game engine with more realistic rendering compared to some of its competitors. You can read more about the CARLA simulator on their official website at https://carla.org. In this section, we will look into how we can create a custom OpenAI Gym-compatible car driving environment to train our learning agents. This is a fairly complex environment and requires a GPU to run—which is unlike other Gym environments we have seen so far. Once you understand how to create a custom environment interface that is Gym-compatible for CARLA, you may well have enough information to develop interfaces for any of your own custom environments, no matter how complex they might be.

The latest version of CARLA is CARLA 0.8.2. While most (if not all)...

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