From Shortest Paths to Reinforcement Learning
Springer International Publishing (Verlag)
978-3-030-61866-7 (ISBN)
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 |
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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 |
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 |
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