Les membres de l'IRIF et les visiteurs sont priés de se conformer aux directives COVID-19 du CNRS et de l'Université de Paris.

Institut de Recherche en Informatique Fondamentale (IRIF)


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L'IRIF est une unité mixte de recherche (UMR 8243) entre le CNRS et l'Université de Paris, qui héberge deux équipes-projets Inria.

Les recherches menées à l'IRIF reposent sur l’étude et la compréhension des fondements de toute l’informatique, afin d’apporter des solutions innovantes aux défis actuels et futurs des sciences numériques.

L'IRIF regroupe près de deux cents personnes. Six de ses membres ont été lauréats de l'European Research Council (ERC), cinq sont membres de l'Institut Universitaire de France (IUF), deux sont membres de l'Academia Europæa, et un est membre de l'Académie des sciences.

Sylvain Schmitz

22.6.2020
Sylvain Schmitz (IRIF) co-organizes the “14th International Conference on Reachability Problems” (RP'20), that is planned to take place either online or at IRIF on October 19-20.

Amos Korman

22.6.2020
Amos Korman (IRIF) will give a talk for receiving the 2020 prize of innovations in distributed computing. It will be broadcast live on Tuesday, June 30, at 7-8 pm (CET). Watching the talk is free of charge, but registration is required.

Tommaso Petrucciani

25.6.2020
Tommaso Petrucciani is awarded the GPL PhD Thesis Prize (Software Engineering and Programming) for his thesis“ “Polymorphic set-theoretic types for functional languages” prepared at IRIF co-supervised by Giuseppe Castagna (IRIF) and Elena Zucca (Università di Genova).

FSCD

15.6.2020
Members of IRIF organize the fifth International Conference on Formal Structures for Computation and Deduction (FSCD) and its affiliated workshops. The event was planned in Paris, due to the pandemic, it is now an online conference held from 06-29 to 07-06.


(Ces actualités sont présentées selon un classement mêlant priorité et aléatoire.)

Tous les évènements sont actuellement organisés à distance.

Vérification
Lundi 6 juillet 2020, 11 heures, (online, using BigBlueButton)
Richard Mayr (University of Edinburgh) Strategy Complexity: Finite Systems vs. Infinite Systems

Consider 2-player perfect information turn-based stochastic games on finite or infinite graphs, and sub-cases (e.g., Markov decision processes (MDPs)). Depending on the objective of the game, optimal strategies (where they exist) and epsilon-optimal strategies may need to use a certain amount/type of memory or to use randomization. This is called the strategy complexity of the objective on the given class of games. We give an overview over the strategy complexity of common objectives on games and MDPs, with a particular focus on the differences between finite-state games/MDPs and infinite-state games/MDPs.