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Abstract: this paper, we survey theoretical foundations of ILP from the viewpoints of Logic of Discovery and Machine Learning, and try to unify these two views with the support of the modern theory of Logic Programming. Firstly, we define several hypothesis construction methods in ILP and give their proof-theoretic foundations by treating them as a procedure which complets incomplete proofs. Next, we discuss the design of individual learning algorithms using these hypothesis construction methods. We... (Update)
Context of citations to this paper: More
.... from Positive Data The problem of synthesizing a loop invariant should have close relationship with that of learning from positive data [2, 5]. In this section, the problem of characterizing reachable states of a state transition system is discussed. This is a problem of nding a...
.... 12, 15, 16] Recently, it is found that a class of learning algorithms for subclasses of first order Horn programs has a common scheme [16, 22], which has its origin in a monotone Boolean DNF learner in [18] Reddy and Tadepalli [16] proposed an algorithm with subsumption...
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BibTeX entry: (Update)
Hiroki Arimura and Akihiro Yamamoto. Inductive Logic Programming: From Logic of Discovery to Machine Learning. IEICE Transactions on Information and Systems, Vol.E83-D, No.1, pp.10-18, 2000. http://citeseer.ist.psu.edu/arimura00inductive.html More
@article{ arimura00inductive,
author = "Hiroki Arimura and Akihiro Yamamoto",
title = "Inductive Logic Programming: {F}rom Logic of Discovery to Machine Learning",
journal = "IEICE Transactions on Information and Systems",
volume = "E83-D",
number = "1",
pages = "10--18",
year = "2000",
url = "citeseer.ist.psu.edu/arimura00inductive.html" }
Citations (may not include all citations):441 Queries and concept learning (context) - Angluin - 1988
388 Inductive logic programming - Muggleton - 1990
267 A note on inductive generalization (context) - Plotkin - 1970
253 A logical framework for default reasoning (context) - Poole - 1988
69 A further note on inductive generalization (context) - Plotkin - 1971
56 Linear resolution for consequence finding (context) - Inoue - 1992
55 Automatic methods of inductive inference (context) - Plotkin - 1971
44 Generalized subsumption and its applications to induction an.. (context) - Buntine - 1988
43 Generalization and learnability: A study of constrained atom.. - Page, Frisch - 1992
43 Classic learning - Frazier, Pitt - 1994
37 Learning from entailment: An application to propositional Ho.. (context) - Frazier, Pitt - 1993
37 Foundations of Inductive Logic Programming (context) - Nienhuys-Cheng, de Wolf - 1997
22 Learning function-free Horn expressions - Khardon - 1998
20 Learning first-order acyclic Horn programs from entailment - Reddy, Tadepalli - 1998
18 Learning unions of tree patterns using queries - Arimura, Ishizaka et al. - 1997
16 Learning acyclic first-order Horn sentences from entailment - Arimura - 1997
11 Anti-unification in constraint logics: Foundations and appli.. (context) - Page - 1993
9 Which hypotheses can be found with inverse entailment - Yamamoto - 1997
7 On inverting generality relations (context) - Jung - 1993
7 Learning Horn definitions with equivalence and membership qu.. - Reddy, Tadepalli - 1997
7 Learning with hints (context) - Angluin - 1988
6 A generalization of the least general generalization - Arimura, Ishizaka et al. - 1994
4 Foundations of Logic Programming: Second (context) - Lloyd - 1987
4 Representing inductive inference with SOLD-resolution - Yamamoto - 1997
3 Inductive resolution (context) - Sato, Akiba - 1993
3 An inference method for the complete inverse of relative sub.. (context) - Yamamoto - 1999
1 Theoretical foundations of inductive logic programming (context) - Yamamoto - 1997
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