Meta-interpretive learning of higher-order dyadic datalog: predicate invention revisited
Gespeichert in:
Verfasser / Beitragende:
[Stephen Muggleton, Dianhuan Lin, Alireza Tamaddoni-Nezhad]
Ort, Verlag, Jahr:
2015
Enthalten in:
Machine Learning, 100/1(2015-07-01), 49-73
Format:
Artikel (online)
Online Zugang:
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| 024 | 7 | 0 | |a 10.1007/s10994-014-5471-y |2 doi |
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| 245 | 0 | 0 | |a Meta-interpretive learning of higher-order dyadic datalog: predicate invention revisited |h [Elektronische Daten] |c [Stephen Muggleton, Dianhuan Lin, Alireza Tamaddoni-Nezhad] |
| 520 | 3 | |a 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 $$H^2_2$$ H 2 2 has universal Turing expressivity though $$H^2_2$$ 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 $$_{D}$$ D to PAC-learn minimal cardinality $$H^2_2$$ H 2 2 definitions. This result is consistent with our experiments which indicate that Metagol $$_{D}$$ D efficiently learns compact $$H^2_2$$ 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. | |
| 540 | |a The Author(s), 2015 | ||
| 690 | 7 | |a Induction |2 nationallicence | |
| 690 | 7 | |a Abduction |2 nationallicence | |
| 690 | 7 | |a Meta-interpretation |2 nationallicence | |
| 690 | 7 | |a Predicate invention |2 nationallicence | |
| 690 | 7 | |a Learning recursion |2 nationallicence | |
| 700 | 1 | |a Muggleton |D Stephen |u Department of Computing, Imperial College London, London, UK |4 aut | |
| 700 | 1 | |a Lin |D Dianhuan |u Department of Computing, Imperial College London, London, UK |4 aut | |
| 700 | 1 | |a Tamaddoni-Nezhad |D Alireza |u Department of Computing, Imperial College London, London, UK |4 aut | |
| 773 | 0 | |t Machine Learning |d Springer US; http://www.springer-ny.com |g 100/1(2015-07-01), 49-73 |x 0885-6125 |q 100:1<49 |1 2015 |2 100 |o 10994 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s10994-014-5471-y |q text/html |z Onlinezugriff via DOI |
| 898 | |a BK010053 |b XK010053 |c XK010000 | ||
| 900 | 7 | |a Metadata rights reserved |b Springer special CC-BY-NC licence |2 nationallicence | |
| 908 | |D 1 |a research-article |2 jats | ||
| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-springer | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.1007/s10994-014-5471-y |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Muggleton |D Stephen |u Department of Computing, Imperial College London, London, UK |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Lin |D Dianhuan |u Department of Computing, Imperial College London, London, UK |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Tamaddoni-Nezhad |D Alireza |u Department of Computing, Imperial College London, London, UK |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Machine Learning |d Springer US; http://www.springer-ny.com |g 100/1(2015-07-01), 49-73 |x 0885-6125 |q 100:1<49 |1 2015 |2 100 |o 10994 | ||