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.

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