Robust Markov Decision Processes with Data-Driven, Distance-Based Ambiguity Sets
We consider finite- and infinite-horizon Markov decision processes (MDPs) with unknown state-transition probabilities. They are assumed to belong to certain ambiguity sets, and the goal is to maxim…
A Simplex Method for Countably Infinite Linear Programs
We introduce a simplex method for general countably infinite linear programs. Previous literature has focused on special cases, such as infinite network flow problems or Markov decision processes. …
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