4 papers
Refinement Type Directed Search for Meta-Interpretive-Learning of Higher-Order Logic Programs
Rolf Morel
The program synthesis problem within the Inductive Logic Programming (ILP) community has typically been seen as untyped. We consider the benefits of user provided types on backgrou…
Learning programs by learning from failures
Andrew Cropper, Rolf Morel
We describe an inductive logic programming (ILP) approach called learning from failures. In this approach, an ILP system (the learner) decomposes the learning problem into three se…
Learning higher-order logic programs
Andrew Cropper, Rolf Morel, Stephen H. Muggleton
A key feature of inductive logic programming (ILP) is its ability to learn first-order programs, which are intrinsically more expressive than propositional programs. In this paper,…
Lower Bounds for Dynamic Programming on Planar Graphs of Bounded Cutwidth
Bas A. M. van Geffen, Bart M. P. Jansen, Arnoud A. W. M. de Kroon +1
Many combinatorial problems can be solved in time on graphs of treewidth , for a problem-specific constant . In several cases, matching upper and lower bounds…