Expected-Cost Analysis for Probabilistic Programs and Semantics-Level Adaption of Optional Stopping Theorems
Di Wang, Jan Hoffmann, Thomas Reps · arXiv (Cornell University) · 2021
In this article, we present a semantics-level adaption of the Optional Stopping Theorem, sketch an expected-cost analysis as its application, and survey different variants of the Optional Stopping Theorem that have been used in static analysis of probabilistic programs.