Hands-On Intelligent Agents with OpenAI Gym: Implement reinforcement learning principles to build artificial intelligence models

Develop, train and test your Deep Reinforcement Learning based AI agentsAbout This Book* Know everything about OpenAI’s open source library Gym and their offerings and services* Learn how to build your own reinforcement learning algorithms and evaluate them for better results* Implement practical examples and get well versed with the working mechanism of reinforcement learning algorithmsWho This Book Is ForThis book is for machine learning developers, game developers and AI enthusiasts who want to get started with OpenAI’s open source library called Gym. If you want to build artificial intelligence agents using reinforcement learning algorithms, then this book is what you need! Some working knowledge of Python programming language is expected to get the most out of the book.What You Will Learn* Get introduced to the OpenAI gym toolkit and learn how to install it on your personal computer.* Learn to train your artificial intelligent agents to master tasks in various OpenAI Gym environments.* Train your agents using reinforcement learning algorithms to solve Mountain car problem.* Implementing your autonomous race-car driving agent using Deep Q-Networks* Design and create your own customized Gym environments* Create a super intelligent agent to beat humans at different Atari games using Actor-Critic algorithms* Learn tips and tricks to solve major challenges using deep reinforcement learning conceptsl.In DetailOpenAI is a leading artificial intelligence company that aims to develop and discover new ways towards safe artificial intelligence. OpenAI’s open source library called Gym helps you achieve great possibilities. With this book, you will be all ready to implement reinforcement learning algorithms at work to build self-evolving agents using OpenAI GymThis book will start with the basics explaining the possibilities and power of OpenAI library called Gym. We will start with an introduction to the OpenAI Gym toolkit and a short brief on reinforcement learning and deep reinforcement learning. The following chapter will be instructing the readers on how to set up the OpenAI gym toolkit on their computers. Following setting up the OpenAI Gym Toolkit, the readers will explore the different OpenAI environments, the tasks they solve and how to help your AI agent to master that task.The reader will then learn to implement an AI agent in the Mountain Car problem, next will be implementing your autonomous race-car driving agent using Deep-Q Networks. Once you have mastered the previous tasks, the next part will be to develop super-intelligent AI agents who can beat humans and achieve much higher scores in Atari games using a state-of-the-art deep reinforcement learning algorithms and OpenAI Gym. The book will then teach the readers the advanced aspects of creating their own customized OpenAI Gym environment. You will then test a reinforcement learning model in that specific environment with the required tips and tricks to solve complex problems using deep reinforcement learning.The readers will then end their journey by getting an insight into the latest developments, tools and the libraries that will be useful to their hands-on deep reinforcement learning skills to the next level.