From Shortest Paths To Reinforcement Learning - Brandimarte Paolo | Libro Springer 01/2021 - HOEPLI.it


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From Shortest Paths to Reinforcement Learning A MATLAB-Based Tutorial on Dynamic Programming




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Dettagli

Genere:Libro
Lingua: Inglese
Editore:

Springer

Pubblicazione: 01/2021
Edizione: 1st ed. 2021





Trama

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.




Sommario

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.




Autore

Paolo Brandimarte is full professor at the Department of Mathematical Sciences of Politecnico di Torino, Italy, where he teaches courses on Business Analytics, Risk Management, and Operations Research. He is the author of more than ten books on the application of optimization and simulation methods to problems ranging from quantitative finance to production and supply chain management.







Altre Informazioni

ISBN:

9783030618667

Condizione: Nuovo
Collana: EURO Advanced Tutorials on Operational Research
Dimensioni: 235 x 155 mm Ø 500 gr
Formato: Copertina rigida
Illustration Notes:67 Illustrations, black and white
Pagine Arabe: 207
Pagine Romane: xi






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