Towards inductive support logic programming

Support logic programming and its practical implementation (Fril) integrates probabilistic and fuzzy uncertainty into logic programming using mass assignments. This paper presents a snapshot of current research, aimed at combining the best aspects of inductive logic programming with the uncertainty representation of Fril to create a sophisticated and novel approach to knowledge discovery. An example is given showing how a supported Fril rule can be extracted from uncertain Fril relations.