Program Induction: Publications
Conference papers
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[1]
Derivation Reduction of Metarules in Meta−interpretive Learning
Andrew Cropper and Sophie Tourret
In Fabrizio Riguzzi‚ Elena Bellodi and Riccardo Zese, editors, Inductive Logic Programming − 28th International Conference‚ ILP 2018‚ Ferrara‚ Italy‚ September 2−4‚ 2018‚ Proceedings. Vol. 11105 of Lecture Notes in Computer Science. Pages 1–21. Springer. 2018.
Details about Derivation Reduction of Metarules in Meta−interpretive Learning | BibTeX data for Derivation Reduction of Metarules in Meta−interpretive Learning | DOI (10.1007/978-3-319-99960-9\_1) | Link to Derivation Reduction of Metarules in Meta−interpretive Learning
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[2]
Logic−Based Inductive Synthesis of Efficient Programs
Andrew Cropper
In Subbarao Kambhampati, editor, Proceedings of the Twenty−Fifth International Joint Conference on Artificial Intelligence‚ IJCAI 2016‚ New York‚ NY‚ USA‚ 9−15 July 2016. Pages 3980–3981. IJCAI/AAAI Press. 2016.
Details about Logic−Based Inductive Synthesis of Efficient Programs | BibTeX data for Logic−Based Inductive Synthesis of Efficient Programs | Link to Logic−Based Inductive Synthesis of Efficient Programs
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[3]
Learning Higher−Order Logic Programs through Abstraction and Invention
Andrew Cropper and Stephen H. Muggleton
In Subbarao Kambhampati, editor, Proceedings of the Twenty−Fifth International Joint Conference on Artificial Intelligence‚ IJCAI 2016‚ New York‚ NY‚ USA‚ 9−15 July 2016. Pages 1418–1424. IJCAI/AAAI Press. 2016.
Details about Learning Higher−Order Logic Programs through Abstraction and Invention | BibTeX data for Learning Higher−Order Logic Programs through Abstraction and Invention | Link to Learning Higher−Order Logic Programs through Abstraction and Invention
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[4]
Typed meta−interpretive learning for proof strategies
Colin Farquhar‚ Gudmund Grov‚ Andrew Cropper‚ Stephen Muggleton and Alan Bundy
In Katsumi Inoue‚ Hayato Ohwada and Akihiro Yamamoto, editors, Late Breaking Papers of the 25th International Conference on Inductive Logic Programming‚ Kyoto University‚ Kyoto‚ Japan‚ August 20th to 22nd‚ 2015.. Vol. 1636 of CEUR Workshop Proceedings. Pages 17–32. CEUR−WS.org. 2015.
Details about Typed meta−interpretive learning for proof strategies | BibTeX data for Typed meta−interpretive learning for proof strategies | Download (pdf) of Typed meta−interpretive learning for proof strategies
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[5]
Meta−Interpretive Learning of Data Transformation Programs
Andrew Cropper‚ Alireza Tamaddoni−Nezhad and Stephen H. Muggleton
In Katsumi Inoue‚ Hayato Ohwada and Akihiro Yamamoto, editors, Inductive Logic Programming − 25th International Conference‚ ILP 2015‚ Kyoto‚ Japan‚ August 20−22‚ 2015‚ Revised Selected Papers. Vol. 9575 of Lecture Notes in Computer Science. Pages 46–59. Springer. 2015.
Details about Meta−Interpretive Learning of Data Transformation Programs | BibTeX data for Meta−Interpretive Learning of Data Transformation Programs | DOI (10.1007/978-3-319-40566-7\_4) | Link to Meta−Interpretive Learning of Data Transformation Programs
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[6]
Learning Efficient Logical Robot Strategies Involving Composable Objects
Andrew Cropper and Stephen H. Muggleton
In Qiang Yang and Michael Wooldridge, editors, Proceedings of the Twenty−Fourth International Joint Conference on Artificial Intelligence‚ IJCAI 2015‚ Buenos Aires‚ Argentina‚ July 25−31‚ 2015. Pages 3423–3429. AAAI Press. 2015.
Details about Learning Efficient Logical Robot Strategies Involving Composable Objects | BibTeX data for Learning Efficient Logical Robot Strategies Involving Composable Objects | Link to Learning Efficient Logical Robot Strategies Involving Composable Objects
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[7]
Learning Efficient Logic Programs
Andrew Cropper
In Qiang Yang and Michael Wooldridge, editors, Proceedings of the Twenty−Fourth International Joint Conference on Artificial Intelligence‚ IJCAI 2015‚ Buenos Aires‚ Argentina‚ July 25−31‚ 2015. Pages 4359–4360. AAAI Press. 2015.
Details about Learning Efficient Logic Programs | BibTeX data for Learning Efficient Logic Programs | Link to Learning Efficient Logic Programs
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[8]
Can predicate invention compensate for incomplete background knowledge?
Andrew Cropper and Stephen Muggleton
In Slawomir Nowaczyk, editor, Thirteenth Scandinavian Conference on Artificial Intelligence − SCAI 2015‚ Halmstad‚ Sweden‚ November 5−6‚ 2015. Vol. 278 of Frontiers in Artificial Intelligence and Applications. Pages 27–36. IOS Press. 2015.
Details about Can predicate invention compensate for incomplete background knowledge? | BibTeX data for Can predicate invention compensate for incomplete background knowledge? | DOI (10.3233/978-1-61499-589-0-27) | Link to Can predicate invention compensate for incomplete background knowledge?
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[9]
Logical Minimisation of Meta−Rules Within Meta−Interpretive Learning
Andrew Cropper and Stephen H. Muggleton
In Jesse Davis and Jan Ramon, editors, Inductive Logic Programming − 24th International Conference‚ ILP 2014‚ Nancy‚ France‚ September 14−16‚ 2014‚ Revised Selected Papers. Vol. 9046 of Lecture Notes in Computer Science. Pages 62–75. Springer. 2014.
Details about Logical Minimisation of Meta−Rules Within Meta−Interpretive Learning | BibTeX data for Logical Minimisation of Meta−Rules Within Meta−Interpretive Learning | DOI (10.1007/978-3-319-23708-4\_5) | Link to Logical Minimisation of Meta−Rules Within Meta−Interpretive Learning
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[10]
Identifying and inferring objects from textual descriptions of scenes from books
Andrew Cropper
In Rumyana Neykova and Nicholas Ng, editors, 2014 Imperial College Computing Student Workshop‚ ICCSW 2014‚ September 25−26‚ 2014‚ London‚ United Kingdom. Vol. 43 of OASICS. Pages 19–26. Schloss Dagstuhl − Leibniz−Zentrum fuer Informatik. 2014.
Details about Identifying and inferring objects from textual descriptions of scenes from books | BibTeX data for Identifying and inferring objects from textual descriptions of scenes from books | DOI (10.4230/OASIcs.ICCSW.2014.19) | Link to Identifying and inferring objects from textual descriptions of scenes from books