BayesL: Towards a Logical Framework for Bayesian Networks
Nicoletti, Stefano M., Stoelinga, Mariëlle
–arXiv.org Artificial Intelligence
We introduce BayesL, a novel logical framework for specifying, querying, and verifying the behaviour of Bayesian networks (BNs). BayesL (pronounced "Basil") is a structured language that allows for the creation of queries over BNs. It facilitates versatile reasoning concerning causal and evidence-based relationships, and permits comprehensive what-if scenario evaluations without the need for manual modifications to the model.
arXiv.org Artificial Intelligence
Jul-1-2025
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- Austria > Vienna (0.14)
- Germany (0.04)
- United Kingdom > England
- Cambridgeshire > Cambridge (0.04)
- Netherlands > Gelderland
- Nijmegen (0.04)
- Europe
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- Research Report (0.40)