TopLog: ILP Using a Logic Program Declarative Bias

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Relating chemical activity to structure: An examination of ILP successes

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Relating chemical activity to structure: An examination of ILP successes

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QG/GA: a stochastic search for Progol

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Demand-Driven Indexing of Prolog Clauses

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Design, Implementation, and Evaluation of a Dynamic Compilation Framework for the YAP System

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Learning Declarative Bias

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Revising First-Order Logic Theories from Examples Through Stochastic Local Search

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ILP :- Just Trie It

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Learning Explanatory Rules from Noisy Data

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Meta-interpretive learning: application to grammatical inference

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Inductive Logic Programming At 30: A New Introduction

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Inductive Logic Programming as Abductive Search

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Data and task parallelism in ILP using MapReduce

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Completing causal networks by meta-level abduction

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Learning Through Hypothesis Refinement Using Answer Set Programming

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SML-Bench – A benchmarking framework for structured machine learning

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Human-Like Rule Learning from Images Using One-Shot Hypothesis Derivation

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Learning Explainable Linguistic Expressions with Neural Inductive Logic Programming for Sentence Classification

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Parameter Screening and Optimisation for ILP Using Designed Experiments

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Mechanizing exploratory game design

Mateas, M., & Smith, A. M. (2012) · Cited by 12 · see citing works

What Kinds of Relational Features Are Useful for Statistical Learning?

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Learning Theories Using Estimation Distribution Algorithms and (Reduced) Bottom Clauses

Pitangui, C. G., & Zaverucha, G. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-31951-8_25 · Cited by 10 · see citing works

MC-TopLog: Complete Multi-clause Learning Guided by a Top Theory

Muggleton, S., Lin, D., & Tamaddoni‐Nezhad, A. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-31951-8_22 · Cited by 9 · see citing works

An Investigation into the Role of Domain-Knowledge on the Use of Embeddings

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Cumulative Learning in the Lambda Calculus

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Top program construction and reduction for polynomial time Meta-Interpretive learning

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SkILL - A Stochastic Inductive Logic Learner

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One-Shot Rule Learning for Challenging Character Recognition

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On Applying Probabilistic Logic Programming to Breast Cancer Data

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Logic-based machine learning using a bounded hypothesis space: the lattice structure, refinement operators and a genetic algorithm approach

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Consensus-based modeling using distributed feature construction with ILP

Dutta, H., & Srinivasan, A. (2017) · Machine Learning · doi:10.1007/s10994-017-5672-2 · Cited by 3 · see citing works

Inductive Logic Programming

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Towards learning to detect meaningful changes in software

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Inductive Logic Programming through Estimation of Distribution Algorithm

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Logic Programs as Declarative and Procedural Bias in Inductive Logic Programming

Lin, D. (2013) · doi:10.25560/24553

Techniques to enhance efficiency and effectiveness of inductive logic programming systems: the TWEETY approaches

Liu, C., & Pontelli, E. (2013) · Journal of Experimental & Theoretical Artificial Intelligence · doi:10.1080/0952813x.2013.808801

Pruning strategies for the efficient traversal of the search space in PILP environments

Côrte-Real, J., Dutra, I., & Rocha, R. (2021) · Knowledge and Information Systems · doi:10.1007/s10115-021-01620-1

TopLog: ILP Using a Logic Program Declarative

Muggleton, S., Santos, J. C. A., & Tamaddoni‐Nezhad, A. (2013)

Generating Declarative Language Bias for Top-Down ILP Algorithms

Kramer, S. (2007)

Logic Programs as Declarative and Procedural Bias in Inductive Logic Programming

Lin, D. (2013) · doi:10.25560/24553

An Alternative to Clause-at-a-Time Hypothesis Construction in Inductive Logic Programming

Anthony, S., Anthony, S., Frisch, A. M., & Frisch, A. M. (2007)

Cautious induction: An alternative to clause-at-a-time hypothesis construction in inductive logic programming

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