Robust Markov Decision Processes

Markov decision processes (MDPs) are powerful tools for decision making in uncertain dynamic environments. However, the solutions of MDPs are of limited practical use because of their sensitivity to distributional model parameters, which are typically unknown and have to be estimated by the decision...

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Bibliographic Details
Published in:Mathematics of operations research 2013-02, Vol.38 (1), p.153-183
Main Authors: Wiesemann, Wolfram, Kuhn, Daniel, Rustem, Breç
Format: Article
Language:English
Subjects:
Ambiguity
Analysis
Approximation
Decision making
Markov analysis
Markov decision processes
Markov processes
Mathematical functions
Mathematical problems
Mathematical theorems
Mathematical vectors
Mathematics
Operations research
Probability
robust optimization
Semidefinite programming
Studies
Transition probabilities
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