Deep Reinforcement Learning

Häftad, Engelska, 2022

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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.

Produktinformation

Utgivningsdatum2022-06-12
Mått155 x 235 x 26 mm
Vikt642 g
FormatHäftad
SpråkEngelska
Antal sidor406
FörlagSpringer Verlag, Singapore
ISBN9789811906374

Tillhör följande kategorier

Systemvetenskap och AI inom Data och it

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.

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.