Induction of Stable Models
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There are many benefits to learning ASP programs.
“There are many benefits to learning ASP programs (Otero, 2001; Law et al., 2014).”
From Inductive Logic Programming At 30: A New Introduction (2022) · cites this paper as Otero, 2001
Cites
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Muggleton, S. (1995) · New Generation Computing · doi:10.1007/bf03037227 · Cited by 1,411 · see citing works
Smodels — an implementation of the stable model and well-founded semantics for normal logic programs
Niemelä, I., & Simons, P. (1997) · Lecture notes in computer science · doi:10.1007/3-540-63255-7_32 · Cited by 324 · see citing works
Nonmonotonic Logic: Context-Dependent Reasoning
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Smodels - An Implementation of the Stable Model and Well-Founded Semantics for Normal LP
Niemelä, I., & Simons, P. (1997) · International Conference on Logic Programming · Cited by 261 · see citing works
Muggleton, S. (1998) · Lecture notes in computer science · doi:10.1007/bfb0027328 · Cited by 19 · see citing works
Inverse Entailment in Nonmonotonic Logic Programs
Sakama, C. (2000) · Lecture notes in computer science · doi:10.1007/3-540-44960-4_13 · Cited by 15 · see citing works
Some Properties of Inverse Resolution in Normal Logic Programs
Sakama, C. (1999) · Lecture notes in computer science · doi:10.1007/3-540-48751-4_26 · Cited by 10 · see citing works
Flagged first, then by citations
1 of the 10 references couldn’t be matched to a known paper.
Research works printed but not linked: 1
- M. Bain and S. Muggleton. Nonmonotonic learning. In S. Muggleton, editor, Inductive Logic Programming, pages 145–161. Academic Press, 1992.
Cited by
Sorted by citations
Nonmonotonic abductive inductive learning
Ray, O. (2008) · Journal of Applied Logic · doi:10.1016/j.jal.2008.10.007 · Cited by 147 · see citing works
Inductive Learning of Answer Set Programs
Law, M., Russo, A., & Broda, K. (2014) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-11558-0_22 · Cited by 133 · 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
“Inducing ASP programs is a relatively new topic (Otero, 2001).”
BackgroundIncremental learning of event definitions with Inductive Logic Programming
Katzouris, N., Artikis, A., & Paliouras, G. (2015) · Machine Learning · doi:10.1007/s10994-015-5512-1 · Cited by 62 · see citing works
Induction from answer sets in nonmonotonic logic programs
Sakama, C. (2005) · ACM Transactions on Computational Logic · doi:10.1145/1055686.1055687 · Cited by 55 · see citing works
Brave induction: a logical framework for learning from incomplete information
Sakama, C., & Inoue, K. (2009) · Machine Learning · doi:10.1007/s10994-009-5113-y · Cited by 45 · see citing works
The complexity and generality of learning answer set programs
Law, M., Russo, A., & Broda, K. B. (2018) · Artificial Intelligence · doi:10.1016/j.artint.2018.03.005 · Cited by 43 · see citing works
Learning weak constraints in answer set programming
LAW, M., RUSSO, A., & BRODA, K. (2015) · Theory and Practice of Logic Programming · doi:10.1017/s1471068415000198 · Cited by 33 · see citing works
Exploiting Answer Set Programming with External Sources for Meta-Interpretive Learning
KAMINSKI, T., EITER, T., & INOUE, K. (2018) · Theory and Practice of Logic Programming · doi:10.1017/s1471068418000261 · Cited by 29 · see citing works
Inductive general game playing
Cropper, A., Evans, R., & Law, M. (2019) · Machine Learning · doi:10.1007/s10994-019-05843-w · Cited by 24 · see citing works
Induction of the Effects of Actions by Monotonic Methods
Otero, R. P. (2003) · Lecture notes in computer science · doi:10.1007/978-3-540-39917-9_20 · Cited by 21 · see citing works
Self-citationLogic-Based Learning of Answer Set Programs
Law, M., Russo, A., & Broda, K. B. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-31423-1_6 · Cited by 21 · see citing works
Schüller, P., & Benz, M. (2018) · Machine Learning · doi:10.1007/s10994-018-5708-2 · Cited by 21 · see citing works
Induction of the Indirect Effects of Actions by Monotonic Methods
Otero, R. P. (2005) · Lecture notes in computer science · doi:10.1007/11536314_17 · Cited by 18 · see citing works
Self-citationLearning Action Descriptions with A-Prolog: Action Language C.
Balduccini, M. (2007) · Cited by 16 · see citing works
Exploiting Answer Set Programming with External Sources for Meta-Interpretive LearningPreprint
Kaminski, T., Eiter, T., & Inoue, K. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1805.00068 · Cited by 13 · see citing works
Meta-Interpretive Learning Using HEX-Programs
Kaminski, T., Eiter, T., & Inoue, K. (2019) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2019/860 · Cited by 8 · see citing works
Incremental and Iterative Learning of Answer Set Programs from Mutually Distinct Examples
Mitra, A., & Baral, C. R. (2018) · Theory and Practice of Logic Programming · doi:10.1017/s1471068418000248 · Cited by 7 · see citing works
Exploiting Answer Set Programming with External Sources for Meta-Interpretive LearningPreprint
Kaminski, T., Eiter, T., & Inoue, K. (2018) · EasyChair preprint · doi:10.29007/drn9 · Cited by 7 · see citing works
Embracing Causality in Inducing the Effects of Actions
Otero, R. P. (2004) · Lecture notes in computer science · doi:10.1007/978-3-540-25945-9_29 · Cited by 4 · see citing works
Self-citationExploring Relations between Answer Set Programs
Inoue, K., & Sakama, C. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-20832-4_7 · Cited by 3 · see citing works
Inductive Equivalence of Logic Programs
Sakama, C., & Inoue, K. (2005) · Lecture notes in computer science · doi:10.1007/11536314_19 · Cited by 2 · see citing works
Inferring process models from temporal data with abduction and induction
Ray, O. (2007) · Bristol Research (University of Bristol) · Cited by 2 · see citing works
Learning Stochastic Logical Automaton
Watanabe, H., & Muggleton, S. (2006) · Lecture notes in computer science · doi:10.1007/11780496_23 · Cited by 2 · see citing works
Inductive equivalence in clausal logic and nonmonotonic logic programming
Sakama, C., & Inoue, K. (2010) · Machine Learning · doi:10.1007/s10994-010-5189-4
Ji, J. (2015)
Learning logic rules from text using statistical methods for natural language processing
Kazmi, M. (2017) · Sabanci University
- Authors
- Otero, R. P.
- Affiliations
- Universidade da Coruña (ES)
- Corresponding author
- Otero, Ramón P.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2001
- Pages
- 193-205
- ISSN
- 0302-9743 (ISSN-L)
- OpenAlex
- W2129247335
- Semantic Scholar
- a36a5c27aa3c63714b5eca1653d25f4b07a353f9
- Cited by
- 27
- References
- 10
- Citations by year
- 2022: 1 · 2019: 3 · 2018: 6 · 2017: 1 · 2015: 3 · 2014: 1
- FWCI
- 0.45
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Lecture notes in computer science (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Logic, Reasoning, and Knowledge
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computability, Logic, AI Algorithms
- Physical Sciences › Computer Science › Artificial Intelligence › Bayesian Modeling and Causal Inference
- Keywords
- inductive logic programming, stable models, normal logic programs, program induction
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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