Foundations of Inductive Logic Programming
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ILP approaches use a language bias to restrict the hypothesis space.
“ILP approaches use a language bias (Nienhuys-Cheng and de Wolf 1997) to restrict the hypothesis space.”
From Learning programs by learning from failures (2021) · cites this paper as Nienhuys-Cheng and de Wolf 1997
If a clause C1 subsumes a clause C2, then C1 entails C2.
“If a clause C 1 subsumes a clause C 2 then C 1 entails C 2 (Nienhuys-Cheng and de Wolf 1997).”
From Learning programs by learning from failures (2021) · cites this paper as Nienhuys-Cheng and de Wolf 1997
Refinement operators for clauses and theories have been studied in detail in ILP.
“By contrast, refinement operators for clauses (Shapiro 1983; De Raedt and Bruynooghe 1993; Nienhuys-Cheng and de Wolf 1997) and theories (Nienhuys-Cheng and de Wolf 1997; Midelfart 1999; Badea 2001) have been studied in detail in ILP.”
From Learning programs by learning from failures (2021) · cites this paper as Nienhuys-Cheng and de Wolf 1997
Reasoning about full clausal logic is computationally expensive.
“However, reasoning about full clausal logic is computationally expensive (Nienhuys-Cheng & Wolf, 1997).”
From Inductive Logic Programming At 30: A New Introduction (2022) · cites this paper as Nienhuys-Cheng & Wolf, 1997
In general, deciding subsumption is a NP-complete problem.
“in general, deciding subsumption is a NP-complete problem (Nienhuys-Cheng & Wolf, 1997).”
From Inductive Logic Programming At 30: A New Introduction (2022) · cites this paper as Nienhuys-Cheng & Wolf, 1997
Cited by
Sorted by citations
Meta-interpretive learning of higher-order dyadic datalog: predicate invention revisited
Muggleton, S. H., Lin, D., & Tamaddoni-Nezhad, A. (2015) · Machine Learning · doi:10.1007/s10994-014-5471-y · Cited by 184 · see citing works
Meta-interpretive learning: application to grammatical inference
Muggleton, S. H., Lin, D., Pahlavi, N., & Tamaddoni-Nezhad, A. (2014) · Machine Learning · doi:10.1007/s10994-013-5358-3 · Cited by 120 · see citing works
Learning programs by learning from failures
Cropper, A., & Morel, R. (2021) · Machine Learning · doi:10.1007/s10994-020-05934-z · Cited by 86 · see citing works
Inductive Logic Programming At 30: A New Introduction
Cropper, A., & Dumančić, S. (2022) · Journal of Artificial Intelligence Research · doi:10.1613/jair.1.13507 · Cited by 83 · see citing works
TopLog: ILP Using a Logic Program Declarative Bias
Muggleton, S. H., Santos, J. C. A., & Tamaddoni-Nezhad, A. (2008) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-89982-2_58 · Cited by 29 · see citing works
Logical reduction of metarules
Cropper, A., & Tourret, S. (2020) · Machine Learning · doi:10.1007/s10994-019-05834-x · Cited by 29 · see citing works
A Bounded Search Space of Clausal Theories
Midelfart, H. (1999) · Lecture Notes in Computer Science · doi:10.1007/3-540-48751-4_20 · Cited by 12 · see citing works
- Authors
- Nienhuys-Cheng, S.-H., & Wolf, R.
- Affiliations
- Carnegie Mellon University (US)
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 1997
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2169042011
- Cited by
- 471
- References
- 0
- Citations by year
- 2026: 3 · 2025: 9 · 2024: 5 · 2023: 12 · 2022: 11 · 2021: 7 · 2020: 7 · 2019: 15 · 2018: 14 · 2017: 6 · 2016: 4 · 2015: 12 · 2014: 11 · 2013: 22 · 2012: 14
- FWCI
- 12.39
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Lecture notes in computer science (publishedVersion)
- UvA-DARE (University of Amsterdam) (submittedVersion)
- Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Logic, Reasoning, and Knowledge
- Physical Sciences › Computer Science › Information Systems › Data Mining Algorithms and Applications
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computability, Logic, AI Algorithms
- Keywords
- inductive logic programming, logic programming, machine learning, inductive reasoning
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