Andrew Cropper

I run the logic and learning (LOL) 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.

Publications

DBLP Scholar
Arxiv 2024 Relational decomposition for program synthesis
Hocquette and Cropper
Arxiv 2024 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

Group members

Previous members