Search Results for author: Andrew Cropper

Found 20 papers, 8 papers with code

Relational program synthesis with numerical reasoning

no code implementations3 Oct 2022 Céline Hocquette, Andrew Cropper

Our approach can identify numerical values in linear arithmetic fragments, such as real difference logic, and from infinite domains, such as real numbers or integers.

Inductive logic programming Program Synthesis +1

Constraint-driven multi-task learning

no code implementations24 Aug 2022 Bogdan Cretu, Andrew Cropper

Inductive logic programming is a form of machine learning based on mathematical logic that generates logic programs from given examples and background knowledge.

Inductive logic programming Multi-Task Learning

Learning programs with magic values

1 code implementation5 Aug 2022 Céline Hocquette, Andrew Cropper

A magic value in a program is a constant symbol that is essential for the execution of the program but has no clear explanation for its choice.

Inductive logic programming Program Synthesis

Learning programs by combining programs

no code implementations1 Jun 2022 Andrew Cropper

The goal of inductive logic programming is to induce a set of rules (a logic program) that generalises examples.

Inductive logic programming Program Synthesis

Learning logic programs through divide, constrain, and conquer

1 code implementation16 Sep 2021 Andrew Cropper

We introduce an inductive logic programming approach that combines classical divide-and-conquer search with modern constraint-driven search.

Inductive logic programming Program Synthesis

Predicate Invention by Learning From Failures

no code implementations29 Apr 2021 Andrew Cropper, Rolf Morel

Discovering novel high-level concepts is one of the most important steps needed for human-level AI.

Inductive logic programming

Learning Logic Programs by Explaining Failures

no code implementations18 Feb 2021 Rolf Morel, Andrew Cropper

We introduce a technique for failure explanation based on analysing SLD-trees.

Inductive logic programming

Learning programs by learning from failures

no code implementations5 May 2020 Andrew Cropper, Rolf Morel

In this approach, an ILP system (the learner) decomposes the learning problem into three separate stages: generate, test, and constrain.

Inductive logic programming

Knowledge Refactoring for Inductive Program Synthesis

1 code implementation21 Apr 2020 Sebastijan Dumancic, Tias Guns, Andrew Cropper

We introduce the \textit{knowledge refactoring} problem, where the goal is to restructure a learner's knowledge base to reduce its size and to minimise redundancy in it.

Inductive logic programming Program induction +1

Learning large logic programs by going beyond entailment

no code implementations21 Apr 2020 Andrew Cropper, Sebastijan Dumančić

We argue that a key limitation of existing systems is that they use entailment to guide the hypothesis search.

Inductive logic programming Program Synthesis

Turning 30: New Ideas in Inductive Logic Programming

no code implementations25 Feb 2020 Andrew Cropper, Sebastijan Dumančić, Stephen H. Muggleton

Common criticisms of state-of-the-art machine learning include poor generalisation, a lack of interpretability, and a need for large amounts of training data.

BIG-bench Machine Learning Inductive logic programming

Forgetting to learn logic programs

2 code implementations15 Nov 2019 Andrew Cropper

To improve learning performance, we explore the idea of forgetting, where a learner can additionally remove programs from its BK.

Inductive logic programming Multi-Task Learning +1

Logical reduction of metarules

no code implementations25 Jul 2019 Andrew Cropper, Sophie Tourret

In general, derivation reduced sets of metarules outperforms subsumption and entailment reduced sets, both in terms of predictive accuracies and learning times.

Inductive logic programming

Learning higher-order logic programs

2 code implementations25 Jul 2019 Andrew Cropper, Rolf Morel, Stephen H. Muggleton

Our theoretical results show that learning higher-order programs, rather than first-order programs, can reduce the textual complexity required to express programs which in turn reduces the size of the hypothesis space and sample complexity.

Inductive logic programming

Inductive general game playing

2 code implementations23 Jun 2019 Andrew Cropper, Richard Evans, Mark Law

This problem is central to inductive general game playing (IGGP).

Inductive logic programming

Playgol: learning programs through play

1 code implementation18 Apr 2019 Andrew Cropper

In this approach, a program induction system (the learner) is given a set of tasks and initial background knowledge.

Inductive logic programming Program induction

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