J
Jean-François Raskin
Researcher at Université libre de Bruxelles
Publications - 306
Citations - 8087
Jean-François Raskin is an academic researcher from Université libre de Bruxelles. The author has contributed to research in topics: Decidability & Markov decision process. The author has an hindex of 47, co-authored 293 publications receiving 7429 citations. Previous affiliations of Jean-François Raskin include Free University of Brussels & Université de Namur.
Papers
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Journal ArticleDOI
Real-Time Model-Checking: Parameters everywhere
TL;DR: This paper presents a method based on automata theoretic principles and an extension of the method to express durations of runs in timed automata using Presburger arithmetic to show that the model-checking problem of TCTL extended with parameters is undecidable over discrete-timed automata with only one parametric clock.
Book ChapterDOI
Variations on the Stochastic Shortest Path Problem
TL;DR: This invited contribution revisits the stochastic shortest path problem, and shows how recent results allow one to improve over the classical solutions: it presents algorithms to synthesize strategies with multiple guarantees on the distribution of the length of paths reaching a given target, rather than simply minimizing its expected value.
Proceedings ArticleDOI
Admissibility in Quantitative Graph Games
TL;DR: In this paper, it was shown that under the assumption that optimal worst-case and cooperative strategies exist, admissible strategies are guaranteed to exist in games of infinite duration with Boolean objectives.
Journal ArticleDOI
The Second Reactive Synthesis Competition (SYNTCOMP 2015)
Swen Jacobs,Roderick Bloem,Romain Brenguier,Robert Könighofer,Guillermo A. Pérez,Jean-François Raskin,Leonid Ryzhyk,Ocan Sankur,Martina Seidl,Leander Tentrup,Adam Walker +10 more
TL;DR: An extension of the authors' benchmark format with meta-information, including a difficulty rating and a reference size for solutions, is introduced to enhance the analysis of experimental results, and the entrants into SYNTCOMP 2015 are described.
Book ChapterDOI
Strategy synthesis for multi-dimensional quantitative objectives
TL;DR: A tight exponential bound is shown on the memory required for finite-memory winning strategies in both multi-dimensional mean-payoff and energy games along with parity objectives, and a complete characterization of when finite memory of strategies can be traded off for randomness is given.