Andrew Cropper : Publications
Journal papers
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[1]
Symbolic metaprogram search improves learning efficiency and explains rule learning in humans
Joshua S. Rule‚ Steven T. Piantadosi‚ Andrew Cropper‚ Kevin Ellis‚ Maxwell Nye and Joshua B. Tenenbaum
In Nature Communications. Vol. 15. No. 1. Pages 6847. 2024.
Details about Symbolic metaprogram search improves learning efficiency and explains rule learning in humans | BibTeX data for Symbolic metaprogram search improves learning efficiency and explains rule learning in humans | DOI (10.1038/s41467-024-50966-x) | Link to Symbolic metaprogram search improves learning efficiency and explains rule learning in humans
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[2]
Learning logic programs by explaining their failures
Rolf Morel and Andrew Cropper
In Mach. Learn.. Vol. 112. No. 10. Pages 3917–3943. 2023.
Details about Learning logic programs by explaining their failures | BibTeX data for Learning logic programs by explaining their failures | DOI (10.1007/S10994-023-06358-1) | Link to Learning logic programs by explaining their failures
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[3]
Learning programs with magic values
Céline Hocquette and Andrew Cropper
In Mach. Learn.. Vol. 112. No. 5. Pages 1551–1595. 2023.
Details about Learning programs with magic values | BibTeX data for Learning programs with magic values | DOI (10.1007/S10994-022-06274-W) | Link to Learning programs with magic values
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[4]
Inductive logic programming at 30
Andrew Cropper‚ Sebastijan Dumancic‚ Richard Evans and Stephen H. Muggleton
In Mach. Learn.. Vol. 111. No. 1. Pages 147–172. 2022.
Details about Inductive logic programming at 30 | BibTeX data for Inductive logic programming at 30 | DOI (10.1007/s10994-021-06089-1) | Link to Inductive logic programming at 30
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[5]
Inductive Logic Programming At 30: A New Introduction
Andrew Cropper and Sebastijan Dumancic
In J. Artif. Intell. Res.. Vol. 74. Pages 765–850. 2022.
Details about Inductive Logic Programming At 30: A New Introduction | BibTeX data for Inductive Logic Programming At 30: A New Introduction | DOI (10.1613/jair.1.13507) | Link to Inductive Logic Programming At 30: A New Introduction
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[6]
Learning programs by learning from failures
Andrew Cropper and Rolf Morel
In Mach. Learn.. Vol. 110. No. 4. Pages 801–856. 2021.
Details about Learning programs by learning from failures | BibTeX data for Learning programs by learning from failures | DOI (10.1007/s10994-020-05934-z) | Link to Learning programs by learning from failures
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[7]
Inductive general game playing
Andrew Cropper‚ Richard Evans and Mark Law
In Mach. Learn.. Vol. 109. No. 7. Pages 1393–1434. 2020.
Details about Inductive general game playing | BibTeX data for Inductive general game playing | DOI (10.1007/s10994-019-05843-w) | Link to Inductive general game playing
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[8]
Logical reduction of metarules
Andrew Cropper and Sophie Tourret
In Mach. Learn.. Vol. 109. No. 7. Pages 1323–1369. 2020.
Details about Logical reduction of metarules | BibTeX data for Logical reduction of metarules | DOI (10.1007/s10994-019-05834-x) | Link to Logical reduction of metarules
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[9]
Learning higher−order logic programs
Andrew Cropper‚ Rolf Morel and Stephen Muggleton
In Mach. Learn.. Vol. 109. No. 7. Pages 1289–1322. 2020.
Details about Learning higher−order logic programs | BibTeX data for Learning higher−order logic programs | DOI (10.1007/s10994-019-05862-7) | Link to Learning higher−order logic programs
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[10]
Learning efficient logic programs
Andrew Cropper and Stephen H. Muggleton
In Machine Learning. Vol. 108. No. 7. Pages 1063–1083. 2019.
Details about Learning efficient logic programs | BibTeX data for Learning efficient logic programs | DOI (10.1007/s10994-018-5712-6) | Link to Learning efficient logic programs
Conference papers
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[1]
Learning Big Logical Rules by Joining Small Rules
Céline Hocquette‚ Andreas Niskanen‚ Rolf Morel‚ Matti Järvisalo and Andrew Cropper
In Kate Larson, editor, Proceedings of the Thirty−Third International Joint Conference on Artificial Intelligence‚ IJCAI−24. Pages 3430–3438. International Joint Conferences on Artificial Intelligence Organization. August, 2024.
Main Track
Details about Learning Big Logical Rules by Joining Small Rules | BibTeX data for Learning Big Logical Rules by Joining Small Rules | DOI (10.24963/ijcai.2024/380) | Link to Learning Big Logical Rules by Joining Small Rules
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[2]
Learning Logic Programs by Discovering Higher−Order Abstractions
Céline Hocquette‚ Sebastijan Dumancic and Andrew Cropper
In Kate Larson, editor, Proceedings of the Thirty−Third International Joint Conference on Artificial Intelligence‚ IJCAI−24. Pages 3421–3429. International Joint Conferences on Artificial Intelligence Organization. August, 2024.
Main Track
Details about Learning Logic Programs by Discovering Higher−Order Abstractions | BibTeX data for Learning Logic Programs by Discovering Higher−Order Abstractions | DOI (10.24963/ijcai.2024/379) | Link to Learning Logic Programs by Discovering Higher−Order Abstractions
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[3]
Learning MDL Logic Programs from Noisy Data
Céline Hocquette‚ Andreas Niskanen‚ Matti Järvisalo and Andrew Cropper
In Michael J. Wooldridge‚ Jennifer G. Dy and Sriraam Natarajan, editors, Thirty−Eighth AAAI Conference on Artificial Intelligence‚ AAAI 2024‚ Thirty−Sixth Conference on Innovative Applications of Artificial Intelligence‚ IAAI 2024‚ Fourteenth Symposium on Educational Advances in Artificial Intelligence‚ EAAI 2014‚ February 20−27‚ 2024‚ Vancouver‚ Canada. Pages 10553–10561. AAAI Press. 2024.
Details about Learning MDL Logic Programs from Noisy Data | BibTeX data for Learning MDL Logic Programs from Noisy Data | DOI (10.1609/AAAI.V38I9.28925) | Link to Learning MDL Logic Programs from Noisy Data
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[4]
Generalisation through Negation and Predicate Invention
David M. Cerna and Andrew Cropper
In Michael J. Wooldridge‚ Jennifer G. Dy and Sriraam Natarajan, editors, Thirty−Eighth AAAI Conference on Artificial Intelligence‚ AAAI 2024‚ Thirty−Sixth Conference on Innovative Applications of Artificial Intelligence‚ IAAI 2024‚ Fourteenth Symposium on Educational Advances in Artificial Intelligence‚ EAAI 2014‚ February 20−27‚ 2024‚ Vancouver‚ Canada. Pages 10467–10475. AAAI Press. 2024.
Details about Generalisation through Negation and Predicate Invention | BibTeX data for Generalisation through Negation and Predicate Invention | DOI (10.1609/AAAI.V38I9.28915) | Link to Generalisation through Negation and Predicate Invention
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[5]
The Automatic Computer Scientist
Andrew Cropper
In Brian Williams‚ Yiling Chen and Jennifer Neville, editors, Thirty−Seventh AAAI Conference on Artificial Intelligence‚ AAAI 2023‚ Thirty−Fifth Conference on Innovative Applications of Artificial Intelligence‚ IAAI 2023‚ Thirteenth Symposium on Educational Advances in Artificial Intelligence‚ EAAI 2023‚ Washington‚ DC‚ USA‚ February 7−14‚ 2023. Pages 15434. AAAI Press. 2023.
Details about The Automatic Computer Scientist | BibTeX data for The Automatic Computer Scientist | DOI (10.1609/AAAI.V37I13.26801) | Link to The Automatic Computer Scientist
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[6]
Learning Logic Programs by Combining Programs
Andrew Cropper and Céline Hocquette
In Kobi Gal‚ Ann Nowé‚ Grzegorz J. Nalepa‚ Roy Fairstein and Roxana Radulescu, editors, ECAI 2023 − 26th European Conference on Artificial Intelligence‚ September 30 − October 4‚ 2023‚ Krakόw‚ Poland − Including 12th Conference on Prestigious Applications of Intelligent Systems (PAIS 2023). Vol. 372 of Frontiers in Artificial Intelligence and Applications. Pages 501–508. IOS Press. 2023.
Details about Learning Logic Programs by Combining Programs | BibTeX data for Learning Logic Programs by Combining Programs | DOI (10.3233/FAIA230309) | Link to Learning Logic Programs by Combining Programs
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[7]
Learning Logic Programs by Discovering Where Not to Search
Andrew Cropper and Céline Hocquette
In Brian Williams‚ Yiling Chen and Jennifer Neville, editors, Thirty−Seventh AAAI Conference on Artificial Intelligence‚ AAAI 2023‚ Thirty−Fifth Conference on Innovative Applications of Artificial Intelligence‚ IAAI 2023‚ Thirteenth Symposium on Educational Advances in Artificial Intelligence‚ EAAI 2023‚ Washington‚ DC‚ USA‚ February 7−14‚ 2023. Pages 6289–6296. AAAI Press. 2023.
Details about Learning Logic Programs by Discovering Where Not to Search | BibTeX data for Learning Logic Programs by Discovering Where Not to Search | DOI (10.1609/AAAI.V37I5.25774) | Link to Learning Logic Programs by Discovering Where Not to Search
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[8]
Relational Program Synthesis with Numerical Reasoning
Céline Hocquette and Andrew Cropper
In Brian Williams‚ Yiling Chen and Jennifer Neville, editors, Thirty−Seventh AAAI Conference on Artificial Intelligence‚ AAAI 2023‚ Thirty−Fifth Conference on Innovative Applications of Artificial Intelligence‚ IAAI 2023‚ Thirteenth Symposium on Educational Advances in Artificial Intelligence‚ EAAI 2023‚ Washington‚ DC‚ USA‚ February 7−14‚ 2023. Pages 6425–6433. AAAI Press. 2023.
Details about Relational Program Synthesis with Numerical Reasoning | BibTeX data for Relational Program Synthesis with Numerical Reasoning | DOI (10.1609/AAAI.V37I5.25790) | Link to Relational Program Synthesis with Numerical Reasoning
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[9]
Learning Logic Programs Though Divide‚ Constrain‚ and Conquer
Andrew Cropper
In Thirty−Sixth AAAI Conference on Artificial Intelligence‚ AAAI 2022‚ Thirty−Fourth Conference on Innovative Applications of Artificial Intelligence‚ IAAI 2022‚ The Twelveth Symposium on Educational Advances in Artificial Intelligence‚ EAAI 2022 Virtual Event‚ February 22 − March 1‚ 2022. Pages 6446–6453. AAAI Press. 2022.
Details about Learning Logic Programs Though Divide‚ Constrain‚ and Conquer | BibTeX data for Learning Logic Programs Though Divide‚ Constrain‚ and Conquer | Link to Learning Logic Programs Though Divide‚ Constrain‚ and Conquer
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[10]
Knowledge Refactoring for Inductive Program Synthesis
Sebastijan Dumancic‚ Tias Guns and Andrew Cropper
In Thirty−Fifth AAAI Conference on Artificial Intelligence‚ AAAI 2021‚ Thirty−Third Conference on Innovative Applications of Artificial Intelligence‚ IAAI 2021‚ The Eleventh Symposium on Educational Advances in Artificial Intelligence‚ EAAI 2021‚ Virtual Event‚ February 2−9‚ 2021. Pages 7271–7278. AAAI Press. 2021.
Details about Knowledge Refactoring for Inductive Program Synthesis | BibTeX data for Knowledge Refactoring for Inductive Program Synthesis | Link to Knowledge Refactoring for Inductive Program Synthesis
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[11]
Turning 30: New Ideas in Inductive Logic Programming
Andrew Cropper‚ Sebastijan Dumancic and Stephen H. Muggleton
In Christian Bessiere, editor, Proceedings of the Twenty−Ninth International Joint Conference on Artificial Intelligence‚ IJCAI 2020. Pages 4833–4839. ijcai.org. 2020.
Details about Turning 30: New Ideas in Inductive Logic Programming | BibTeX data for Turning 30: New Ideas in Inductive Logic Programming | DOI (10.24963/ijcai.2020/673) | Link to Turning 30: New Ideas in Inductive Logic Programming
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[12]
Learning Large Logic Programs By Going Beyond Entailment
Andrew Cropper and Sebastijan Dumancic
In Christian Bessiere, editor, Proceedings of the Twenty−Ninth International Joint Conference on Artificial Intelligence‚ IJCAI 2020. Pages 2073–2079. ijcai.org. 2020.
Details about Learning Large Logic Programs By Going Beyond Entailment | BibTeX data for Learning Large Logic Programs By Going Beyond Entailment | DOI (10.24963/ijcai.2020/287) | Link to Learning Large Logic Programs By Going Beyond Entailment
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[13]
Learning Higher−Order Programs through Predicate Invention
Andrew Cropper‚ Rolf Morel and Stephen H. Muggleton
In The Thirty−Fourth AAAI Conference on Artificial Intelligence‚ AAAI 2020‚ The Thirty−Second Innovative Applications of Artificial Intelligence Conference‚ IAAI 2020‚ The Tenth AAAI Symposium on Educational Advances in Artificial Intelligence‚ EAAI 2020‚ New York‚ NY‚ USA‚ February 7−12‚ 2020. Pages 13655–13658. AAAI Press. 2020.
Details about Learning Higher−Order Programs through Predicate Invention | BibTeX data for Learning Higher−Order Programs through Predicate Invention | Link to Learning Higher−Order Programs through Predicate Invention
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[14]
Forgetting to Learn Logic Programs
Andrew Cropper
In The Thirty−Fourth AAAI Conference on Artificial Intelligence‚ AAAI 2020‚ The Thirty−Second Innovative Applications of Artificial Intelligence Conference‚ IAAI 2020‚ The Tenth AAAI Symposium on Educational Advances in Artificial Intelligence‚ EAAI 2020‚ New York‚ NY‚ USA‚ February 7−12‚ 2020. Pages 3676–3683. AAAI Press. 2020.
Details about Forgetting to Learn Logic Programs | BibTeX data for Forgetting to Learn Logic Programs | Link to Forgetting to Learn Logic Programs
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[15]
Playgol: Learning Programs Through Play
Andrew Cropper
In Sarit Kraus, editor, Proceedings of the Twenty−Eighth International Joint Conference on Artificial Intelligence‚ IJCAI 2019‚ Macao‚ China‚ August 10−16‚ 2019. Pages 6074–6080. ijcai.org. 2019.
Details about Playgol: Learning Programs Through Play | BibTeX data for Playgol: Learning Programs Through Play | DOI (10.24963/ijcai.2019/841) | Link to Playgol: Learning Programs Through Play
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[16]
Typed Meta−interpretive Learning of Logic Programs
Rolf Morel‚ Andrew Cropper and C.−H. Luke Ong
In Francesco Calimeri‚ Nicola Leone and Marco Manna, editors, Logics in Artificial Intelligence − 16th European Conference‚ JELIA 2019‚ Rende‚ Italy‚ May 7−11‚ 2019‚ Proceedings. Vol. 11468 of Lecture Notes in Computer Science. Pages 198–213. Springer. 2019.
Details about Typed Meta−interpretive Learning of Logic Programs | BibTeX data for Typed Meta−interpretive Learning of Logic Programs | DOI (10.1007/978-3-030-19570-0) | Link to Typed Meta−interpretive Learning of Logic Programs
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[17]
SLD−Resolution Reduction of Second−Order Horn Fragments
Sophie Tourret and Andrew Cropper
In Francesco Calimeri‚ Nicola Leone and Marco Manna, editors, Logics in Artificial Intelligence − 16th European Conference‚ JELIA 2019‚ Rende‚ Italy‚ May 7−11‚ 2019‚ Proceedings. Vol. 11468 of Lecture Notes in Computer Science. Pages 259–276. Springer. 2019.
Details about SLD−Resolution Reduction of Second−Order Horn Fragments | BibTeX data for SLD−Resolution Reduction of Second−Order Horn Fragments | DOI (10.1007/978-3-030-19570-0) | Link to SLD−Resolution Reduction of Second−Order Horn Fragments
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[18]
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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[19]
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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[20]
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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[21]
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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[22]
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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[23]
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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[24]
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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[25]
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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[26]
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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[27]
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