SOURCE-LINKED INTELLIGENCE

COntext-free model checking for Recursive PrObabilistic pRogrAms

CORDIS · observation · Publication date unknown

COntext-free model checking for Recursive PrObabilistic pRogrAms IoT and embedded systems are powered by increasingly sophisticated software components, employing machine learning to create devices that perform activities once exclusively carried out by humans. Since these activities may involve significant risks and responsibilities, ensuring the correctness and safety of involved software components is crucial. Probabilistic Programs (PPs) are often employed in AI-powered software, particularly to exploit Bayesian inference, and to model randomized algorithms. Thus, studying verification of PPs can enable verification techniques for ensuring safety and correctness of AI-powered programs. PPs are computer programs that, besides ordinary programming constructs, may contain random choices, and variable assignments according to a random distribution. The CORPORA (COntext-free model checking for Recursive PrObabilistic pRogrAms) project aims at developing new techniques for the verification of Recursive Probabilistic Programs, one of the most expres

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recordType

award

status

SIGNED

region

EU

value

183600.96

unit

EUR