An Introduction to Deep Reinforcement Learning

Abstract

Deep reinforcement learning is the combination of reinforcement learning (RL) and deep learning. This field of research has been able to solve a wide range of complex decision-making tasks that were previously out of reach for a machine. Thus, deep RL opens up many new applications in domains such as healthcare, robotics, smart grids, finance, and many more. This manuscript provides an 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. We assume the reader is familiar with basic machine learning concepts.

Keywords

Reinforcement learningArtificial intelligenceComputer scienceDeep learningGeneralizationField (mathematics)RoboticsMachine learningRobotMathematics

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Publication Info

Year: 2018
Type: article
Volume: 11
Issue: 3-4
Pages: 219-354
Citations: 1163
Access: Closed

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APA Style

                            
                                
                                    Vincent François-Lavet, 
                                
                                    Peter Henderson, 
                                
                                    Riashat Islam
                                
                                et al.
                            
                            (2018). 
                            An Introduction to Deep Reinforcement Learning. 
                            Foundations and Trends® in Machine Learning
                            , 11
                            (3-4)
                            , 219-354.
                            https://doi.org/10.1561/2200000071
                        

Identifiers

DOI: 10.1561/2200000071