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Key benefits

Second edition of the bestselling introduction to deep reinforcement learning, expanded with six new chapters

Learn advanced exploration techniques including noisy networks, pseudo-count, and network distillation methods

Apply RL methods to cheap hardware robotics platforms

Description

Deep Reinforcement Learning Hands-On, Second Edition is an updated and expanded version of the bestselling guide to the very latest reinforcement learning (RL) tools and techniques. It provides you with an introduction to the fundamentals of RL, along with the hands-on ability to code intelligent learning agents to perform a range of practical tasks. With six new chapters devoted to a variety of up-to-the-minute developments in RL, including discrete optimization (solving the Rubik's Cube), multi-agent methods, Microsoft's TextWorld environment, advanced exploration techniques, and more, you will come away from this book with a deep understanding of the latest innovations in this emerging field. In addition, you will gain actionable insights into such topic areas as deep Q-networks, policy gradient methods, continuous control problems, and highly scalable, non-gradient methods. You will also discover how to build a real hardware robot trained with RL for less than $100 and solve the Pong environment in just 30 minutes of training using step-by-step code optimization. In short, Deep Reinforcement Learning Hands-On, Second Edition, is your companion to navigating the exciting complexities of RL as it helps you attain experience and knowledge through real-world examples.

What you will learn

Understand the deep learning context of RL and implement complex deep learning models

Evaluate RL methods including cross-entropy, DQN, actor-critic, TRPO, PPO, DDPG, D4PG, and others

Build a practical hardware robot trained with RL methods for less than $100

Discover Microsoft s TextWorld environment, which is an interactive fiction games platform

Use discrete optimization in RL to solve a Rubik s Cube

Teach your agent to play Connect 4 using AlphaGo Zero

Explore the very latest deep RL research on topics including AI chatbots

Discover advanced exploration techniques, including noisy networks and network distillation techniques

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

AI Assistant (beta) to help accelerate your learning

Frequently bought together

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Total € 138.97

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Machiel Kruger Feb 22, 2024

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Oren Zeev-Ben-Mordehai Feb 24, 2024

I enjoy the reading and I'm learning exactly what I was looking for and much more relevant material.

vincent tanoe Mar 03, 2020

I like the way the book is written and the explanation are well detailed !

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Keadtipoom Aug 25, 2021

Good book, read and run too easy.

MrWiddles Jun 06, 2021

As an IT person I had used supervised and unsupervised learning before but not RL. This book has good plain english engineering descriptions of the problem and solution as well as the maths. Rather than starting with descriptions of abstract models it shows how different challenges can be physically solved which is important in getting the first foothold of understanding the concepts of the game.I like the way it uses many illustrations and describes how a student could start using python libs to do testing. High res colour would have been nice but in practice not an issue for me.My personal interest is Smart Cities, Digital Twins and how RL can solve real world problems.

Deep Reinforcement Learning Hands-On: Apply modern RL methods to practical problems of chatbots, robotics, discrete optimization, web automation, and more , Second Edition

What do you get with eBook?