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Multistage stochastic programming: A scenario tree based approach to planning under uncertainty
Defourny, Boris; Ernst, Damien; Wehenkel, Louis
2011In Sucar, L. Enrique; Morales, Eduardo F.; Hoey, Jesse (Eds.) Decision Theory Models for Applications in Artificial Intelligence: Concepts and Solutions
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Keywords :
Sequential decision making under uncertainty; scenario tree generation; validation of approximate solutions
Abstract :
[en] In this chapter, we present the multistage stochastic programming framework for sequential decision making under uncertainty. We discuss its differences with Markov Decision Processes, from the point of view of decision models and solution algorithms. We describe the standard technique for solving approximately multistage stochastic problems, which is based on a discretization of the disturbance space called scenario tree. We insist on a critical issue of the approach: the decisions can be very sensitive to the parameters of the scenario tree, whereas no efficient tool for checking the quality of approximate solutions exists. In this chapter, we show how supervised learning techniques can be used to evaluate reliably the quality of an approximation, and thus facilitate the selection of a good scenario tree. The framework and solution techniques presented in the chapter are explained and detailed on several examples. Along the way, we define notions from decision theory that can be used to quantify, for a particular problem, the advantage of switching to a more sophisticated decision model.
Research center :
Systems and Modeling Research Unit
Disciplines :
Computer science
Author, co-author :
Defourny, Boris ;  Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Dép. d'électric., électron. et informat. (Inst.Montefiore)
Ernst, Damien  ;  Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation
Wehenkel, Louis  ;  Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation
Language :
English
Title :
Multistage stochastic programming: A scenario tree based approach to planning under uncertainty
Publication date :
2011
Main work title :
Decision Theory Models for Applications in Artificial Intelligence: Concepts and Solutions
Editor :
Sucar, L. Enrique
Morales, Eduardo F.
Hoey, Jesse
Publisher :
Information Science Publishing, Hershey, United States - Pennsylvania
ISBN/EAN :
978-1609601652
Peer reviewed :
Peer reviewed
Funders :
DYSCO (Dynamical Systems, Control, and Optimization); FRS-FNRS; PASCAL2 Network of Excellence
Available on ORBi :
since 26 December 2010

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