ForM-SMArt
Financiado
Formal Methods for Stochastic Models Algorithms and Applications
The formal analysis of stochastic models plays an important role in different disciplines of science, e.g., probability theory, evolutionary stochastic processes in biology. In computer science, such models arise in formal verific...
The formal analysis of stochastic models plays an important role in different disciplines of science, e.g., probability theory, evolutionary stochastic processes in biology. In computer science, such models arise in formal verification of probabilistic systems, analysis of probabilistic programs, analysis of game-theoretic interactions with stochastic aspects, reasoning about randomized protocols, etc. At the heart of the analysis methods are algorithmic approaches that lead to automated tools. Despite significant and impressive research achievements over the decades, many fundamental algorithmic problems related to formal analysis of stochastic models remain open. Moreover, the emergence of new technologies and the need to build more complex systems, require faster and scalable algorithmic solutions. The overarching theme of the project is algorithmic approaches for formal methods to analyse stochastic models. Our main research aims are:
(1) Finite-state models: Develop faster explicit and implicit algorithms, and establish conditional lower bounds, for finite-state probabilistic systems.
(2) Probabilistic programs: Develop efficient algorithmic approaches and practical techniques (e.g., compositional and abstraction techniques) for the analysis of probabilistic programs.
(3) Stochastic and evolutionary games: Develop algorithmic approaches related to stochastic games and evolutionary games, which bring together the two different fields of game theory.
(4) Application domains: Explore new application areas in diverse domains to demonstrate the effectiveness of the new algorithms developed.
The project’s success will significantly enrich formal methods for analysis of stochastic models that are crucial in the development of robust and correct systems. Since stochastic models are foundational in several disciplines, the new algorithmic solutions are expected to lead to automated tools beneficial to other disciplines.
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Duración del proyecto: 71 meses
Fecha Inicio: 2020-01-22
Fecha Fin: 2025-12-31
Fecha Fin: 2025-12-31
Línea de financiación: concedida
El organismo H2020 notifico la concesión del proyecto el día 2020-01-22
Línea de financiación objetivo
El proyecto se financió a través de la siguiente ayuda:
ERC-2019-COG:
ERC Consolidator Grant
Cerrada
hace 5 años
Presupuesto
El presupuesto total del proyecto asciende a
2M€
Líder del proyecto
INSTITUTE OF SCIENCE AND TECHNOLOGY AUSTRIA
No se ha especificado una descripción o un objeto social para esta compañía.
Perfil tecnológico
TRL
4-5
Perfil tecnológico
TRL
4-5
328.40K€ |
Participante