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

Content Provider	Springer Nature Link
Author	Muggleton, Stephen H. Lin, Dianhuan Tamaddoni Nezhad, Alireza
Copyright Year	2015
Abstract	Since the late 1990s predicate invention has been under-explored 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 metalogical substitutions with respect to a modified Prolog meta-interpreter which acts as the learning engine. New predicate symbols are introduced as constants representing existentially quantified higher-order variables. The approach demonstrates that predicate invention can be treated as a form of higher-order logical reasoning. 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 $$H^2_2$$ has universal Turing expressivity though $$H^2_2$$ is decidable given a finite signature. Additionally we show that Knuth–Bendix ordering of the hypothesis space together with logarithmic clause bounding allows our MIL implementation Metagol $$_{D}$$ to PAC-learn minimal cardinality $$H^2_2$$ definitions. This result is consistent with our experiments which indicate that Metagol $$_{D}$$ efficiently learns compact $$H^2_2$$ definitions involving predicate invention for learning robotic strategies, the East–West train challenge and NELL. Additionally higher-order concepts were learned in the NELL language learning domain. The Metagol code and datasets described in this paper have been made publicly available on a website to allow reproduction of results in this paper.
Starting Page	49
Ending Page	73
Page Count	25
File Format	PDF
ISSN	08856125
Journal	Machine Learning
Volume Number	100
Issue Number	1
e-ISSN	15730565
Language	English
Publisher	Springer US
Publisher Date	2015-03-12
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Induction Abduction Meta-interpretation Predicate invention Learning recursion Artificial Intelligence (incl. Robotics) Control, Robotics, Mechatronics Computing Methodologies Simulation and Modeling Language Translation and Linguistics
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Software

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