Nonmonotonic Inductive Logic Programming (invited talk)
Proceedings of the 6th International Conference on
Logic Programming and Nonmonotonic Reasoning (LPNMR'01),
Lecture Notes in Artificial Intelligence 2173, pages 62-80,
Nonmonotonic logic programming (NMLP)
and inductive logic programming (ILP)
are two important extensions of logic programming.
The former aims at representing incomplete knowledge and reasoning with
commonsense, while the latter targets the problem of inductive construction
of a general theory from examples and background knowledge.
NMLP and ILP thus have seemingly different motivations and goals, but
they have much in common in the background of problems, and
techniques developed in each field are related to one another.
%both handle nonmonotonic problems and perform hypothetical reasoning in
%incomplete knowledge bases.
This paper presents techniques for combining these
two fields of logic programming in the context of
nonmonotonic inductive logic programming (NMILP).
We review recent results and problems to realize NMILP.
Full Paper (gzipped postscript 184K)
Slide (pdf 280K)