Risk aversion to parameter uncertainty in Markov decision processes with an application to slow-onset disaster relief
M Meraklı, S Küçükyavuz - IISE Transactions, 2020 - Taylor & Francis
Abstract In classic Markov Decision Processes (MDPs), action costs and transition
probabilities are assumed to be known, although an accurate estimation of these …
probabilities are assumed to be known, although an accurate estimation of these …
Stochastic Dynamic Optimization Under Ambiguity
L Steimle - 2019 - deepblue.lib.umich.edu
Stochastic dynamic optimization methods are powerful mathematical tools for informing
sequential decision-making in environments where the outcomes of decisions are uncertain …
sequential decision-making in environments where the outcomes of decisions are uncertain …