From Shortest Paths to Reinforcement Learning

A MATLAB-Based Tutorial on Dynamic Programming

Paolo Brandimarte (Autor)

Buch | Hardcover

XI, 207 Seiten

2021 | 1st ed. 2021
Springer International Publishing (Verlag)
978-3-030-61866-7 (ISBN)

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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.

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.

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.

Erscheinungsdatum	13.01.2021
Reihe/Serie	EURO Advanced Tutorials on Operational Research
Zusatzinfo	XI, 207 p. 67 illus.
Verlagsort	Cham
Sprache	englisch
Maße	155 x 235 mm
Gewicht	500 g
Themenwelt	Wirtschaft ► Allgemeines / Lexika
Themenwelt	Wirtschaft ► Betriebswirtschaft / Management
Schlagworte	Approximate Dynamic Programming • Asset Allocation • Decision Rules • dynamic optimization • Dynamic Programming • Engineering Economics • Inventory Management • machine learning • Matlab programming • Monte Carlo simulation • Numerical optimization methods • optimal control • Option pricing • Parallel Computing • Quantitative Finance • Reinforcement Learning • Resource budgeting • Revenue Management • stochastic optimization
ISBN-10	3-030-61866-8 / 3030618668
ISBN-13	978-3-030-61866-7 / 9783030618667
Zustand	Neuware