Semantic Scholar Open Access 2018 1447 sitasi

An Introduction to Deep Reinforcement Learning

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

Lihat Sumber DOI

Abstrak

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.

Topik & Kata Kunci

Computer Science Mathematics

Penulis (5)

Vincent François-Lavet

Peter Henderson

Riashat Islam

Marc G. Bellemare

Joelle Pineau

Format Sitasi

APA MLA BibTeX

François-Lavet, V., Henderson, P., Islam, R., Bellemare, M.G., Pineau, J. (2018). An Introduction to Deep Reinforcement Learning. https://doi.org/10.1561/2200000071

Akses Cepat

Lihat di Sumber doi.org/10.1561/2200000071

Informasi Jurnal

Tahun Terbit: 2018
Bahasa: en
Total Sitasi: 1447×
Sumber Database: Semantic Scholar
DOI: 10.1561/2200000071
Akses: Open Access ✓