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Training Reinforcement Learning Agents Using OpenAI Gym

The OpenAI Gym provides a lot of virtual environments to train your reinforcement learning agents. In reinforcement learning, the most difficult task is to create the environment. This is where OpenAI Gym comes to the rescue, by providing a lot of toy game environments to provide users with a platform to train and benchmark their reinforcement learning agents.

In other words, it provides a playground for the reinforcement learning agent to learn and benchmark their performance, where the agent has to learn to navigate from the start state to the goal state without undergoing any mishaps.

Thus, in this chapter, we will be learning to understand and use environments from OpenAI Gym and trying to implement basic Q-learning and the Q-network for our agents to learn.

OpenAI Gym provides different types of environments. They...

Key benefits

Explore reinforcement learning concepts and their implementation using TensorFlow

Discover different problem-solving methods for reinforcement learning

Apply reinforcement learning to autonomous driving cars, robobrokers, and more

Description

Reinforcement learning (RL) allows you to develop smart, quick and self-learning systems in your business surroundings. It's an effective method for training learning agents and solving a variety of problems in Artificial Intelligence - from games, self-driving cars and robots, to enterprise applications such as data center energy saving (cooling data centers) and smart warehousing solutions. The book covers major advancements and successes achieved in deep reinforcement learning by synergizing deep neural network architectures with reinforcement learning. You'll also be introduced to the concept of reinforcement learning, its advantages and the reasons why it's gaining so much popularity. You'll explore MDPs, Monte Carlo tree searches, dynamic programming such as policy and value iteration, and temporal difference learning such as Q-learning and SARSA. You will use TensorFlow and OpenAI Gym to build simple neural network models that learn from their own actions. You will also see how reinforcement learning algorithms play a role in games, image processing and NLP. By the end of this book, you will have gained a firm understanding of what reinforcement learning is and understand how to put your knowledge to practical use by leveraging the power of TensorFlow and OpenAI Gym.

Who is this book for?

If you want to get started with reinforcement learning using TensorFlow in the most practical way, this book will be a useful resource. The book assumes prior knowledge of machine learning and neural network programming concepts, as well as some understanding of the TensorFlow framework. No previous experience of reinforcement learning is required.

What you will learn

Implement state-of-the-art reinforcement learning algorithms from the basics

Discover various reinforcement learning techniques such as MDP, Q Learning, and more

Explore the applications of reinforcement learning in advertisement, image processing, and NLP

Teach a reinforcement learning model to play a game using TensorFlow and OpenAI Gym

Understand how reinforcement learning applications are used in robotics

What do you get with eBook?

Instant access to your Digital eBook purchase

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

Frequently bought together

Hands-On Reinforcement Learning with Python

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Total € 108.97 Stars icon

RT Aug 26, 2018

Das Buch ist zu oberflächlich - die Konzepte werden nur unzureichend erklärt.Der Beispielcode ist nicht sinnvoll.Ich habe das Buch an Amazon zurückgeschickt

Amazon Verified review

Giang Dao Aug 19, 2018

Not even re-produce quality paper result

Santhosh Jul 23, 2018

Not a good book to learn reinforcement learning or tensorflow. It does not discuss programming either. The book could be improved with an insight into the reinforcement learning concepts, at least to help the reader understand the concepts intuitively.

siva Jul 17, 2018

Must have book for RL learners

Gadginir Jun 17, 2018

Book is above average after going through first 4 chapters. I felt it takes lot of time to understand the concepts. You will take 30 min to go through 2-3 pages sometime. With some more good examples, author can make it bit easier.

Reinforcement Learning with TensorFlow: A beginner's guide to designing self-learning systems with TensorFlow and OpenAI Gym

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Reinforcement Learning with TensorFlow

Training Reinforcement Learning Agents Using OpenAI Gym

The OpenAI Gym

Programming an agent using an OpenAI Gym environment

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Reinforcement Learning with TensorFlow: A beginner's guide to designing self-learning systems with TensorFlow and OpenAI Gym

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