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From Shortest Paths to Reinforcement Learning : A MATLAB-Based Tutorial on Dynamic Programming / by Paolo Brandimarte
(EURO Advanced Tutorials on Operational Research. ISSN:23646888)

Publisher (Cham : Springer International Publishing : Imprint: Springer)
Year 2021
Edition 1st ed. 2021.
Authors *Brandimarte, Paolo author
SpringerLink (Online service)

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OB00144640 Springer Business and Management eBooks (電子ブック) 9783030618674

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Material Type E-Book
Media type 機械可読データファイル
Size XI, 207 p. 67 illus : online resource
Notes The dynamic programming principle -- Implementing dynamic programming -- Modeling for dynamic programming -- Numerical dynamic programming for discrete states -- Approximate dynamic programming and reinforcement learning for discrete states -- Numerical dynamic programming for continuous states -- Approximate dynamic programming and reinforcement learning for continuous states
Dynamic programming (DP) has a relevant history as a powerful and flexible optimization principle, but has a bad reputation as a computationally impractical tool. This book fills a gap between the statement of DP principles and their actual software implementation. Using MATLAB throughout, this tutorial gently gets the reader acquainted with DP and its potential applications, offering the possibility of actual experimentation and hands-on experience. The book assumes basic familiarity with probability and optimization, and is suitable to both practitioners and graduate students in engineering, applied mathematics, management, finance and economics
HTTP:URL=https://doi.org/10.1007/978-3-030-61867-4
Subjects LCSH:Operations research
LCSH:Decision making
LCSH:Management science
LCSH:Economic theory
LCSH:Numerical analysis
LCSH:Economics, Mathematical 
LCSH:Engineering economics
LCSH:Engineering economy
FREE:Operations Research/Decision Theory
FREE:Operations Research, Management Science
FREE:Economic Theory/Quantitative Economics/Mathematical Methods
FREE:Numerical Analysis
FREE:Quantitative Finance
FREE:Engineering Economics, Organization, Logistics, Marketing
Classification LCC:HD30.23
DC23:658.40301
ID 8000072901
ISBN 9783030618674

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