Discovering rules to design newspapers: An inductive constraint logic programming approach
Bernard Marc, Francois Jacquenet Lirsia
Abstract
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Bernard Marc, Francois Jacquenet Lirsia
Abstract
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Inductive logic programming combines both machine learning and logic programming techniques. ILP uses first-order predicate logic restricted to Horn clauses as an underlying language. Thus, programs induced by an ILP system inherit the classical limitations of PROLOG programs. Constraint logic programming avoids some of the limitations of logic programming, and so ILP aims to induce programs that employ this paradigm. Current ILP systems that induce constrained logic programs extend systems based on the normal semantics ofILP. In this article we introduce IC-Log, a new system that induces constrained logic programs and relies on an extension ofa nonmonotonic semantics-based system. We then present an application of IC-Log in the field ofcomputer-aided publishing.
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Inductive logic programming combines both machine learning and logic programming techniques. ILP uses first-order predicate logic restricted to Horn clauses as an underlying language. Thus, programs induced by an ILP system inherit the classical limitations of PROLOG programs. Constraint logic programming avoids some of the limitations of logic programming, and so ILP aims to induce programs that employ this paradigm. Current ILP systems that induce constrained logic programs extend systems based on the normal semantics ofILP. In this article we introduce IC-Log, a new system that induces constrained logic programs and relies on an extension ofa nonmonotonic semantics-based system. We then present an application of IC-Log in the field ofcomputer-aided publishing.
Key concepts: Prolog, Logic programming, Computer science, Concurrent constraint logic programming, Horn clause, Inductive logic programming, Programming language, Constraint logic programming