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Deep Reinforcement Learning

BuchKartoniert, Paperback
406 Seiten
Englisch
Springererschienen am12.06.20221st ed. 2022
Deep reinforcement learning has attracted considerable attention recently. Biology has inspired the creation of artificial neural networks and deep learning, while psychology studies how animals and humans learn, and how subjects´ desired behavior can be reinforced with positive and negative stimuli.mehr
Verfügbare Formate
BuchKartoniert, Paperback
EUR53,49
E-BookPDF1 - PDF WatermarkE-Book
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Produkt

KlappentextDeep reinforcement learning has attracted considerable attention recently. Biology has inspired the creation of artificial neural networks and deep learning, while psychology studies how animals and humans learn, and how subjects´ desired behavior can be reinforced with positive and negative stimuli.
Details
ISBN/GTIN978-981-19-0637-4
ProduktartBuch
EinbandartKartoniert, Paperback
Verlag
Erscheinungsjahr2022
Erscheinungsdatum12.06.2022
Auflage1st ed. 2022
Seiten406 Seiten
SpracheEnglisch
IllustrationenXV, 406 p. 1 illus.
Artikel-Nr.16501296

Inhalt/Kritik

Inhaltsverzeichnis
1. Introduction.- 2. Tabular Value-Based Methods.- 3. Approximating the Value Function.- 4. Policy-Based Methods.- 5. Model-Based Methods.- 6. Two-Agent Reinforcement Learning.- 7. Multi-Agent Reinforcement Learning.- 8. Hierarchical Reinforcement Learning.- 9. Meta Learning.- 10. Further Developments.- A. Deep Reinforcement Learning Suites.- B. Deep Learning.- C. Mathematical Background.mehr

Autor

Aske Plaat is a Professor of Data Science at Leiden University and scientific director of the Leiden Institute of Advanced Computer Science (LIACS). He is co-founder of the Leiden Centre of Data Science (LCDS) and initiated SAILS, a multidisciplinary program on artificial intelligence. His research interests include reinforcement learning, combinatorial games and self-learning systems. He is the author of Learning to Play (published by Springer in 2020), which specifically covers reinforcement learning and games.