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Interactive Concept-Learning and Constructive Induction by Analogy
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“Metarules (Cropper and Tourret 2020) are another popular syntactic bias used by many ILP approaches (De Raedt and Bruynooghe 1992; Wang et al. 2014; Albarghouthi et al. 2017; Kaminski et al. 2018), including Metagol (Muggleton et al. 2015; Cropper et al. 2020; Cropper and Muggleton 2016) and, to an extent 5 , ∂ ILP (Evans and Grefenstette 2018).”
From Learning programs by learning from failures (2021) · cites this paper as De Raedt and Bruynooghe 1992
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Langley, P. (1988) · Machine Learning · doi:10.1007/bf00115008 · Cited by 187
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Cited by
Sorted by citations
Learning programs by learning from failures
Cropper, A., & Morel, R. (2021) · Machine Learning · doi:10.1007/s10994-020-05934-z · Cited by 86
“Metarules (Cropper and Tourret 2020) are another popular syntactic bias used by many ILP approaches (De Raedt and Bruynooghe 1992; Wang et al. 2014; Albarghouthi et al. 2017; Kaminski et al. 2018), including Metagol (Muggleton et al. 2015; Cropper et al. 2020; Cropper and Muggleton 2016) and, to an…”
BackgroundInductive 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
“Metarules are also called program schemata (Flener, 1996) and second-order schemata (De Raedt & Bruynooghe, 1992), amongst many other names.”
BackgroundLogical reduction of metarules
Cropper, A., & Tourret, S. (2020) · Machine Learning · doi:10.1007/s10994-019-05834-x · Cited by 29
Learning higher-order logic programs
Cropper, A., Morel, R., & Muggleton, S. (2020) · Machine Learning · doi:10.1007/s10994-019-05862-7 · Cited by 11
“Early work in ILP (Flener and Yilmaz 1999; De Raedt and Bruynooghe 1992; Emde et al. 1983) used higher-order formulas to specify the overall form of programs to be learned, similar to howMIL uses metarules.”
Method
Metadata
- Authors
- de Raedt, L., & Bruynooghe, M.
- Affiliations
- KU Leuven (BE)
- ORCID
- Bruynooghe, Maurice
- Venue
- Machine Learning
- Published
- 1992-03
- Volume
- 8
- Issue
- 2
- Pages
- 107-150
- ISSN
- 0885-6125 (ISSN-L)
- 1573-0565
- OpenAlex
- W2093252035
- Cited by
- 65
- References
- 2
- Citations by year
- 2025: 1 · 2024: 1 · 2023: 2 · 2022: 2 · 2021: 1 · 2020: 1 · 2019: 4 · 2018: 2
- FWCI
- 7.78
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Machine Learning (publishedVersion)
- Lirias (KU Leuven) (submittedVersion, other-oa)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning and Algorithms
- Physical Sciences › Computer Science › Artificial Intelligence › AI-based Problem Solving and Planning
- Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning and Data Classification
- Keywords
- constructive induction, example generation, error recovery
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