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2015
ACM

Meta-interpretive learning of higher-order dyadic datalog: predicate invention revisited

3 years 4 months ago
Meta-interpretive learning of higher-order dyadic datalog: predicate invention revisited
In recent years Predicate Invention has been underexplored within Inductive Logic Programming due to difficulties in formulating efficient search mechanisms. However, a recent paper demonstrated that both predicate invention and the learning of recursion can be efficiently implemented for regular and context-free grammars, by way of abduction with respect to a meta-interpreter. New predicate symbols are introduced as constants representing existentially quantified higher-order variables. In this paper we generalise the approach of Meta-Interpretive Learning (MIL) to that of learning higher-order dyadic datalog programs. We show that with an infinite signature the higher-order dyadic datalog class H2 2 has universal Turing expressivity though H2 2 is decidable given a finite signature. Additionally we show that Knuth-Bendix ordering of the hypothesis space together with logarithmic clause bounding allows our Dyadic MIL implementation MetagolD to PAC-learn minimal cardinailty H2 2...
Stephen H. Muggleton, Dianhuan Lin, Alireza Tamadd
Added 14 Apr 2016
Updated 14 Apr 2016
Type Journal
Year 2015
Where ML
Authors Stephen H. Muggleton, Dianhuan Lin, Alireza Tamaddoni-Nezhad
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