Christos Dimitrakakis & Ronald Ortner 
Decision Making Under Uncertainty and Reinforcement Learning [PDF ebook] 
Theory and Algorithms

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This book presents recent research in decision making under uncertainty, in particular reinforcement learning and learning with expert advice. The core elements of decision theory, Markov decision processes and reinforcement learning have not been previously collected in a concise volume. Our aim with this book was to provide a solid theoretical foundation with elementary proofs of the most important theorems in the field, all collected in one place, and not typically found in
introductory textbooks.  This book is addressed to graduate students that are interested in statistical decision making under uncertainty and the foundations of reinforcement learning.  

€149.79
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Table des matières

Introduction.- Subjective probability and utility.- Decision problems.- Estimation.

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Langue Anglais ● Format PDF ● Pages 243 ● ISBN 9783031076145 ● Taille du fichier 3.5 MB ● Maison d’édition Springer International Publishing ● Lieu Cham ● Pays CH ● Publié 2022 ● Téléchargeable 24 mois ● Devise EUR ● ID 8732193 ● Protection contre la copie DRM sociale

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