Inductive logic programming (ILP) and machine learning together represent a powerful synthesis of symbolic reasoning and statistical inference. ILP focuses on deriving interpretable logic rules from ...

Picat is a new logic-based programming language. In many ways, Picat is similar to Prolog, especially B-Prolog, but it has functions in addition to predicates, pattern-matching instead of unification ...

Start working toward program admission and requirements right away. Work you complete in the non-credit experience will transfer to the for-credit experience when you ...

The field of interpretability investigates what machine learning (ML) models are learning from training datasets, the causes and effects of changes within a model, and the justifications behind its ...

Start working toward program admission and requirements right away. Work you complete in the non-credit experience will transfer to the for-credit experience when you ...