P
Petr Novotny
Researcher at Institute of Science and Technology Austria
Publications - 7
Citations - 108
Petr Novotny is an academic researcher from Institute of Science and Technology Austria. The author has contributed to research in topics: Time complexity & Probabilistic logic. The author has an hindex of 5, co-authored 7 publications receiving 104 citations.
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Algorithmic Analysis of Qualitative and Quantitative Termination Problems for Affine Probabilistic Programs
TL;DR: In this article, the authors considered the problem of proving termination of probabilistic programs with real-valued variables and used the notion of ranking supermartingales, which is a powerful approach for proving termination.
Proceedings Article
Lexicographic Ranking Supermartingales: An Efficient Approach to Termination of Probabilistic Programs
TL;DR: In this paper, the authors introduce lexicographic supermartingales (RSMs) for probabilistic programs with nondeterminism and show that they can be used for compositional reasoning about almost-sure termination.
Proceedings Article
Optimizing Expectation with Guarantees in POMDPs
TL;DR: This work goes beyond both the “expectation” and “threshold” approaches and considers a “guaranteed payoff optimization (GPO)” problem for POMDPs, where the objective is to find a policy σ such that each possible outcome yields a discounted-sum payoff of at least t.
Proceedings ArticleDOI
Long-Run Average Behaviour of Probabilistic Vector Addition Systems
TL;DR: It is shown that for one-counter pVASS, the pattern frequency vector is defined and takes one of finitely many values for almost all runs, and these values and their associated probabilities can be approximated up to an arbitrarily small relative error in polynomial time.
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Long-Run Average Behaviour of Probabilistic Vector Addition Systems
TL;DR: In this article, the pattern frequency vector for runs in probabilistic vector addition systems with states (pVASSs) is studied, where each configuration of a given pVASS is assigned one of finitely many patterns and every run can thus be seen as an infinite sequence of these patterns.