3 papers
cs.AI2025
BayesL: a Logical Framework for the Verification of Bayesian Networks
Stefano M. Nicoletti, E. Moritz Hahn, Mariëlle Stoelinga
Modern explainable AI still struggles with a fundamental gap: although Bayesian networks (BNs) provide transparent probabilistic structure, there is no unified way to formally expr…
cs.AI2024
WATCHDOG: an ontology-aWare risk AssessmenT approaCH via object-oriented DisruptiOn Graphs
Stefano M. Nicoletti, E. Moritz Hahn, Mattia Fumagalli +2
When considering risky events or actions, we must not downplay the role of involved objects: a charged battery in our phone averts the risk of being stranded in the desert after a…
cs.LO2024
Tools at the Frontiers of Quantitative Verification
Roman Andriushchenko, Alexander Bork, Carlos E. Budde +20
The analysis of formal models that include quantitative aspects such as timing or probabilistic choices is performed by quantitative verification tools. Broad and mature tool suppo…