Vorträge und Posterpräsentationen (mit Tagungsband-Eintrag):
A. Kofnov, M. Moosbrugger, S. Stankovic, E. Bartocci, E. Bura:
"Moment-based Invariants for Probabilistic Loops with non-polynomial assignments";
als Vortrag angenommen für: Proc. of QEST 2022: the 19th International Conference on Quantitative Evaluation of SysTems,
Warsaw, Poland;
12.09.2022
- 16.09.2022; in: "Proc. of QEST'22: the 19th International Conference on Quantitative Evaluation of SysTems",
(2022).
Kurzfassung englisch:
We present a method to automatically approximate moment-based invariants of probabilistic programs with non-polynomial updates of continuous state variables to accommodate more complex dynamics. Our approach leverages polynomial chaos expansion to approximate non-linear functional updates as sums of orthogonal polynomials. We exploit this result to automatically estimate state-variable moments of all orders in Prob-solvable loops with non-polynomial updates. We showcase the accuracy of our estimation approach in several examples, such as the turning vehicle model and the Taylor rule in monetary policy.