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Nicolas Markey

Researcher at University of Rennes

Publications -  163
Citations -  3649

Nicolas Markey is an academic researcher from University of Rennes. The author has contributed to research in topics: Model checking & Timed automaton. The author has an hindex of 34, co-authored 154 publications receiving 3439 citations. Previous affiliations of Nicolas Markey include University of Orléans & École Normale Supérieure.

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Book ChapterDOI

Infinite Runs in Weighted Timed Automata with Energy Constraints

TL;DR: This work considers automata equipped with positive and negative weights on transitions and locations, corresponding to the production and consumption of some resource, and asks the question whether there exists an infinite path for which the accumulated weight for any finite prefix satisfies certain constraints.
Proceedings ArticleDOI

Temporal logic with forgettable past

TL;DR: This work investigates NLTL, a linear-time temporal logic with forgettable past, and provides optimal automata-theoretic algorithms for these EXPSPACE-complete problems.
Journal ArticleDOI

Improved undecidability results on weighted timed automata

TL;DR: This paper presents a new approach for prediction of the links leading to relevant pages based on a Hidden Markov Model (HMM), and demonstrates that this approach performs better than Context-Graph crawling and Best-First crawling.
Book ChapterDOI

Model Checking Timed Automata with One or Two Clocks

TL;DR: This paper studies model checking of timed automata (TAs) and aims at finding efficient model checking for subclasses of TAs, and considers model checking TCTL and T CTL ≤,≥ over TAs with one clock or two clocks.
Book ChapterDOI

ATL with Strategy Contexts and Bounded Memory

TL;DR: The alternating-time temporal logics ATL and ATL * are extended with strategy contexts and memory constraints : the first extension makes strategy quantifiers to not "forget" the strategies being executed by the other players and the second extension allows strategy quantifier to restrict to memoryless or bounded-memory strategies.