Andrew Cropper
I am a junior research fellow at the University of Oxford.
I design machine learning algorithms that learn to write computer programs.
I focus on inductive logic programming (ILP), which combines machine learning and mathematical logic.
I developed the ILP systems Metagol and Popper.
Email
CV
Publications
DBLP
Scholar
Journals

Inductive general game playing
A. Cropper, R. Evans, and M. Law
Machine learning 2020
slides
code
dataset

Logical minimisation of metarules
A. Cropper and S. Tourret
Machine learning 2020
slides
code

Learning higherorder logic programs
A. Cropper, R. Morel, and S.H. Muggleton
Machine learning 2020
slides
code

Learning efficient logic programs
A. Cropper and S.H. Muggleton
Machine learning 2019
slides
code
Conferences

Learning large logic programs by going beyond entailment
A. Cropper and S. Dumančić
IJCAI 2020

Turning 30: new ideas in inductive logic programming
A. Cropper, Dumančić, and S.H. Muggleton
IJCAI 2020

Forgetting to learn logic programs
A. Cropper
AAAI 2020
slides
code

Learning higherorder programs through predicate invention
A. Cropper, R. Morel, and S.H. Muggleton
AAAI 2020
slides

Playgol: learning programs through play
A. Cropper
IJCAI 2019
slides
code

SLDresolution reduction of secondorder horn fragments
S. Tourret and A. Cropper
JELIA 2019

Typed metainterpretive learning of logic programs
R. Morel, A. Cropper, and L. Ong
JELIA 2019
slides
code

Derivation reduction of metarules in metainterpretive learning
A. Cropper and S. Tourret
ILP 2018
slides
code

Learning higherorder logic programs through abstraction and invention
A. Cropper and S.H. Muggleton
IJCAI 2016
slides
code

Logicbased inductive synthesis of efficient programs
A. Cropper
IJCAI 2016
slides

Learning efficient logical robot strategies involving composable objects
A. Cropper and S.H. Muggleton
IJCAI 2015
slides
code

Learning efficient logic programs
A. Cropper
IJCAI 2015
slides

Metainterpretive learning of data transformation programs
A. Cropper, A. TamaddoniNezhad, and S.H. Muggleton
ILP 2015
slides
code

Typed metainterpretive learning for proof strategies
C. Farquhar, G. Grov, A. Cropper, S.H. Muggleton, and A. Bundy
ILP 2015

Can predicate invention compensate for incomplete background knowledge?
A. Cropper and S.H. Muggleton
SCAI 2015
slides

Logical minimisation of metarules within metainterpretive learning
A. Cropper and S.H. Muggleton
ILP 2014
slides
Workshops

SLDresolution reduction of secondorder Horn fragments
S. Tourret and A. Cropper
Termgraph 2018

Identifying and inferring objects from textual descriptions of scenes from books
A. Cropper
ICCSW 2014
slides
Others

Learning programs by learning from failures
A. Cropper and R. Morel
Under review

Knowledge refactoring for program induction
S. Dumančić and A. Cropper
In preparation.

Inductive logic programming at 30: a new introduction
A. Cropper and S. Dumančić.
In preparation.
Theses

Efficiently learning efficient programs
A. Cropper.
PhD thesis, Imperial College London, 2017.

Modelling stock volume using Twitter
A. Cropper.
MSc thesis, University of Oxford, 2011.
Talks
 Learning higherorder logic programs
KU Leuven, 2019.
 Inductive general game playing
KU Leuven, 2019.
 Playgol: learning programs through play
KU Leuven, 2019.
 Inductive general game playing
MIT, 2019.
 Playgol: learning programs through play
MIT, 2019.
 Playgol: learning programs through play
Machine intelligence 21, 2019.
 Inductive general game playing
Dagstuhl, 2019.
 Playgol: learning programs through play
Dagstuhl, 2019.
 Learning algorithms using logic
University of Oxford, 2019.
 Learning efficient logic programs
MIT, 2018.
 Learning efficient logic programs
Dagstuhl, 2017.

Learning higherorder logic programs
Dagstuhl, 2017.
 Learning efficient logic programs
Machine intelligence 20, 2016.
 Logicbased learning of programs.
UC Berkeley, 2016.
 Metagol.
Dagstuhl, 2015.
 Predicate invention in metainterpretive learning.
Wakayama University, Japan, 2014.