Andrew Cropper

I run the logic and learning group at the University of Oxford. We work on inductive logic programming (ILP), which combines logic and machine learning. We develop the ILP system Popper.

andrew.cropper@cs.ox.ac.uk

Publications

DBLP | Scholar

Arxiv	Honey, I shrunk the hypothesis space (through logical preprocessing) Cropper, Gouveia, and Cerna
Arxiv	An empirical comparison of cost functions in inductive logic programming Hocquette and Cropper
Arxiv	Efficient rule induction by ignoring pointless rules Cropper and Cerna
Arxiv	Can humans teach machines to code? Hocquette, Langer, Cropper, and Schmid
IJCAI 2025	Relational decomposition for program synthesis Hocquette and Cropper
AAAI 2025	Scalable knowledge refactoring using constrained optimisation Liu, Cerna, Gouveia, and Cropper
Nature Comms 2024	Symbolic metaprogram search improves learning efficiency and explains rule learning in humans Rule, Piantadosi, Cropper, Ellis, Nye, and Tenenbaum
ECAI 2024	Learning logic programs by finding minimal unsatisfiable subprograms Cropper and Hocquette
IJCAI 2024	Learning big logical rules by joining small rules Hocquette, Niskanen, Morel, Järvisalo, and Cropper
IJCAI 2024	Learning logic programs by discovering higher-order abstractions Hocquette, Dumančić, and Cropper
AAAI 2024	Learning MDL logic programs from noisy data Hocquette, Niskanen, Järvisalo, and Cropper
AAAI 2024	Generalisation through negation and predicate invention Cerna and Cropper
ECAI 2023	Learning logic programs by combining programs Cropper and Hocquette
AAAI 2023	Relational program synthesis with numerical reasoning Hocquette and Cropper
AAAI 2023	Learning logic programs by discovering where not to search Cropper and Hocquette
AAAI 2023	The automatic computer scientist Cropper
MLJ 2023	Learning programs by explaining failures Morel and Cropper
MLJ 2023	Learning programs with magic values Hocquette and Cropper
AAAI 2022	Learning logic programs through divide, constrain, and conquer Cropper
JAIR 2022	Inductive logic programming at 30: a new introduction Cropper and Dumančić
MLJ 2022	Inductive logic programming at 30 Cropper, Dumančić, Evans, and Muggleton
AAAI 2021	Knowledge refactoring for inductive program synthesis Dumančić, Guns, and Cropper
MLJ 2021	Learning programs by learning from failures Cropper and Morel
IJCAI 2020	Learning large logic programs by going beyond entailment Cropper and Dumančić
IJCAI 2020	Turning 30: new ideas in inductive logic programming Cropper, Dumančić, and Muggleton
AAAI 2020	Forgetting to learn logic programs Cropper
AAAI 2020	Learning higher-order programs through predicate invention Cropper, Morel, and Muggleton
MLJ 2020	Inductive general game playing Cropper, Evans, and Law
MLJ 2020	Logical reduction of metarules Cropper and Tourret
MLJ 2020	Learning higher-order logic programs Cropper, Morel, and Muggleton
IJCAI 2019	Playgol: learning programs through play Cropper
JELIA 2019	SLD-resolution reduction of second-order Horn fragments Tourret and Cropper
JELIA 2019	Typed meta-interpretive learning of logic programs Morel, Cropper, and Ong
MLJ 2019	Learning efficient logic programs Cropper and Muggleton
ILP 2018	Derivation reduction of metarules in meta-interpretive learning Cropper and Tourret
IJCAI 2016	Learning higher-order logic programs through abstraction and invention Cropper and Muggleton
IJCAI 2016	Logic-based inductive synthesis of efficient programs Cropper
IJCAI 2015	Learning efficient logical robot strategies involving composable objects Cropper and Muggleton
IJCAI 2015	Learning efficient logic programs Cropper
ILP 2015	Meta-interpretive learning of data transformation programs Cropper, Tamaddoni-Nezhad, and Muggleton
ILP 2015	Typed meta-interpretive learning for proof strategies Farquhar, Grov, Cropper, Muggleton, and Bundy
SCAI 2015	Can predicate invention compensate for incomplete background knowledge? Cropper and Muggleton
ILP 2014	Logical minimisation of meta-rules within meta-interpretive learning Cropper and Muggleton