An Introduction to Deep Reinforcement Learning

Download or Read eBook An Introduction to Deep Reinforcement Learning PDF written by Vincent Francois-Lavet and published by Foundations and Trends (R) in Machine Learning. This book was released on 2018-12-20 with total page 156 pages. Available in PDF, EPUB and Kindle.
An Introduction to Deep Reinforcement Learning
Author :
Publisher : Foundations and Trends (R) in Machine Learning
Total Pages : 156
Release :
ISBN-10 : 1680835386
ISBN-13 : 9781680835380
Rating : 4/5 (86 Downloads)

Book Synopsis An Introduction to Deep Reinforcement Learning by : Vincent Francois-Lavet

Book excerpt: Deep reinforcement learning is the combination of reinforcement learning (RL) and deep learning. This field of research has recently been able to solve a wide range of complex decision-making tasks that were previously out of reach for a machine. Deep RL opens up many new applications in domains such as healthcare, robotics, smart grids, finance, and many more. This book provides the reader with a starting point for understanding the topic. Although written at a research level it provides a comprehensive and accessible introduction to deep reinforcement learning models, algorithms and techniques. Particular focus is on the aspects related to generalization and how deep RL can be used for practical applications. Written by recognized experts, this book is an important introduction to Deep Reinforcement Learning for practitioners, researchers and students alike.


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Revised and expanded to include multi-agent methods, discrete optimization, RL in robotics, advanced exploration techniques, and more Key Features Second editio