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/game theory
- /natural sciences/mathematics/applied mathematics/statistics and probability
- /natural sciences/computer and information sciences
Call for proposal
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