An introduction to deep reinforcement learning

Vincent François-Lavet, Peter Henderson, Riashat Islam, Marc G. Bellemare, Joelle Pineau

Research output: Contribution to journalArticlepeer-review

719 Scopus citations

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 decisionmaking 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.

Original languageEnglish (US)
Pages (from-to)219-354
Number of pages136
JournalFoundations and Trends in Machine Learning
Volume11
Issue number3-4
DOIs
StatePublished - Dec 20 2018
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Artificial Intelligence

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