inductive logic programming

Research on transfer learning attempts to apply previously acquired knowledge to new learning tasks. Working within this area, we report on a procedure that learns and transfers constraints in the context of inductive process modeling.

We introduce an inductive logic programming approach to learning declarative bias. Results indicate that the bias reduces the size of the search space without removing the most accurate structures.