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 |