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Formal Methods for Stochastic Models: Algorithms and Applications

Project description

Powerful new algorithms will reduce the impact of chance on predictability

If all of life’s outputs were fully determined by their inputs and the starting conditions, things would be a lot simpler. Fortunately, understanding situations and predicting outcomes when some inherent randomness plays a role has been simplified by stochastic models. As computing power increases together with available data for inputs across numerous disciplines, more powerful, robust and accurate algorithms are in high demand. The EU-funded ForM-SMArt project is tackling this important challenge, developing algorithmic approaches for formal methods to analyse stochastic models that will lead to enhanced utility of automated tools. The outcomes will be a breath of fresh air for fields from basic and applied mathematics and engineering to evolutionary biology and finance.

Field of science

  • /natural sciences/mathematics/applied mathematics/statistics and probability
  • /natural sciences/mathematics/applied mathematics/game theory

Call for proposal

ERC-2019-COG
See other projects for this call

Funding Scheme

ERC-COG - Consolidator Grant
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Host institution

INSTITUTE OF SCIENCE AND TECHNOLOGY AUSTRIA
Address
Am Campus 1
3400 Klosterneuburg
Austria
Activity type
Higher or Secondary Education Establishments
EU contribution
€ 1 997 918

Beneficiaries (1)

INSTITUTE OF SCIENCE AND TECHNOLOGY AUSTRIA
Austria
EU contribution
€ 1 997 918
Address
Am Campus 1
3400 Klosterneuburg
Activity type
Higher or Secondary Education Establishments