Stephen Muggleton

Stephen Muggleton, Wayne Luk, Andreas Fidjeland, 2002, 2002 IEEE International Conference on Field-Programmable Technology, 2002. (FPT). Proceedings..

From ILP to PILP

Stephen Muggleton, 2008, SBIA.

Latest Advances in Inductive Logic Programming, ILP 2011, Late Breaking Papers, Windsor Great Park, UK, July 31 - August 3, 2011

Stephen Muggleton, Hiroaki Watanabe, 2014, ILP.

Optimal Layered Learning: A PAC Approach to Incremental Sampling

Stephen Muggleton, 1993, ALT.

Drug design using inductive logic programming

Stephen Muggleton, Michael J. E. Sternberg, C. Feng, 1993, [1993] Proceedings of the Twenty-sixth Hawaii International Conference on System Sciences.

Learning Structure and Parameters of Stochastic Logic Programs

Stephen Muggleton, S. Muggleton, 2002, ILP.

Inductive programming meets the real world

Sumit Gulwani, Stephen Muggleton, José Hernández-Orallo, 2015, Commun. ACM.

Completing Inverse Entailment

Stephen Muggleton, 1998, ILP.

Learning from Positive Data

Stephen Muggleton, S. Muggleton, 1996, Inductive Logic Programming Workshop.

Bayesian Inductive Logic Programming

Stephen Muggleton, 1994, ICML.

Inductive Logic Programming: 21st International Conference, ILP 2011, Windsor Great Park, UK, July 31 -- August 3, 2011

Stephen Muggleton, Francesca A. Lisi, Alireza Tamaddoni-Nezhad, 2012 .

Protein Fold Discovery Using Stochastic Logic Programs

Stephen Muggleton, Michael J. E. Sternberg, Lawrence A. Kelley, 2008, Probabilistic Inductive Logic Programming.

The Predictive Toxicology Evaluation Challenge

Ashwin Srinivasan, Stephen Muggleton, Ross D. King, 1997, IJCAI.

Machine Intelligibility and the Duality Principle

Stephen Muggleton, Donald Michie, D. Michie, 1997, Software Agents and Soft Computing.

ILP turns 20 - Biography and future challenges

Katsumi Inoue, Ashwin Srinivasan, Ivan Bratko, 2012, Mach. Learn..

05051 Abstracts Collection - Probabilistic, Logical and Relational Learning - Towards a Synthesis

Luc De Raedt, Thomas G. Dietterich, Stephen Muggleton, 2005, Probabilistic, Logical and Relational Learning.

Modelling Metabolic Pathways Using Stochastic Logic Programs-Based Ensemble Methods

Stephen Muggleton, Huma Lodhi, S. Muggleton, 2004, CMSB.

Towards Machine Learning of Predictive Models from Ecological Data

Stephen Muggleton, Alireza Tamaddoni-Nezhad, David Bohan, 2014, ILP.

Alan Turing and the development of Artificial Intelligence

Stephen Muggleton, S. Muggleton, 2014, AI Commun..

The Complexity of Translating BLPs to RMMs

Stephen Muggleton, Niels Pahlavi, S. Muggleton, 2007, ILP.

Inductive Logic Programming: Issues, Results and the Challenge of Learning Language in Logic

Stephen Muggleton, S. Muggleton, 1999, Artif. Intell..

Learning Programs in the Event Calculus

Stephen Muggleton, Stephen Moyle, S. Muggleton, 1997, ILP.

The cycle of abductive and inductive knowledge development

Koichi Furukawa, Stephen Muggleton, Donald Michie, 2000 .

Subsumer: A Prolog theta-subsumption engine

Stephen Muggleton, Jose Santos, 2010, ICLP.

Customisable Multi-Processor Acceleration of Inductive Logic Programming

Stephen Muggleton, Wayne Luk, Andreas K. Fidjeland, 2011, ILP.

Learning Higher-Order Programs through Predicate Invention

Stephen Muggleton, Rolf Morel, Andrew Cropper, 2020, AAAI.

Computational Systems Biology

Stephen Muggleton, Huma Lodhi, S. Muggleton, 2010 .

Towards Inductive Generalization in Higher Order Logic

Stephen Muggleton, Cao Feng, S. Muggleton, 1992, ML.

Knowledge Discovery in Biological and Chemical Domains

Stephen Muggleton, S. Muggleton, 1998, Discovery Science.

Machine Learning and biomolecular modelling

Stephen Muggleton, Ross D. King, Michael J. E. Sternberg, 1992, Machine Intelligence 13.

Can ILP Learn Complete and Correct Game Strategies?

Stephen Muggleton, Changze Xu, 2011, ILP.

Probabilistic, Logical and Relational Learning - A Further Synthesis, 15.04. - 20.04.2007

Luc De Raedt, Thomas G. Dietterich, Kristian Kersting, 2008, Probabilistic, Logical and Relational Learning - A Further Synthesis.

Meta-interpretive learning of higher-order dyadic datalog: predicate invention revisited

Stephen Muggleton, Dianhuan Lin, S. Muggleton, 2013, Machine Learning.

ProGolem: A System Based on Relative Minimal Generalisation

Stephen Muggleton, Alireza Tamaddoni-Nezhad, Jose Santos, 2009, ILP.

Learning to Relate Terms in a Multiple Agent Environment

Stephen Muggleton, Pavel Brazdil, 1991, EWSL.

Logical Minimisation of Meta-Rules Within Meta-Interpretive Learning

Stephen Muggleton, Andrew Cropper, S. Muggleton, 2014, ILP.

Inverting the resolution principle

Stephen Muggleton, S. Muggleton, 1991 .

Applications of inductive logic programming

Ivan Bratko, Stephen Muggleton, I. Bratko, 1995, SGAR.

Inductive Logic Programming: Theory and Methods

Luc De Raedt, Stephen Muggleton, S. Muggleton, 1994, J. Log. Program..

Correction to: How Much Can Experimental Cost Be Reduced in Active Learning of Agent Strategies?

Stephen Muggleton, Céline Hocquette, 2018 .

Machine Discovery of Comprehensible Strategies for Simple Games Using Meta-interpretive Learning

Stephen Muggleton, Céline Hocquette, 2019, New Generation Computing.

Learning Chomsky-like Grammars for Biological Sequence Families

Ashwin Srinivasan, Stephen Muggleton, Christopher H. Bryant, 2000, ICML.

Guest editorial: special issue on Inductive Logic Programming (ILP 2011)

Stephen Muggleton, Jianzhong Chen, 2012, Machine Learning.

Multi-class Prediction Using Stochastic Logic Programs

Stephen Muggleton, Michael J. E. Sternberg, Lawrence A. Kelley, 2007, ILP.

Editors's Introduction to the Special Issue on "100 Years of Alan Turing and 20 Years of SLAIS"

Ivan Bratko, Dunja Mladenic, Stephen Muggleton, 2013, Informatica.

A Strategy for Constructing New Predicates in First-Order Logic

Stephen Muggleton, S. Muggleton, 1988, EWSL.

Use of Inductive Logic Programming to Learn Principles of Protein Structure

Stephen Muggleton, Michael J. E. Sternberg, Marcel Turcotte, 2000, Electron. Trans. Artif. Intell..

Application of abductive ILP to learning metabolic network inhibition from temporal data

Stephen Muggleton, Antonis C. Kakas, Alireza Tamaddoni-Nezhad, 2006, Machine Learning.

Meta-Interpretive Learning from noisy images

Zhi-Hua Zhou, Stephen Muggleton, Alireza Tamaddoni-Nezhad, 2018, Machine Learning.

ILP for Mathematical Discovery

Stephen Muggleton, Simon Colton, S. Muggleton, 2003, ILP.

Special Issue on Semantic Technology

Freddy Lecue, Stephen Muggleton, Dongyan Zhao, 2019, New Generation Computing.

Inverse entailment and progol

Stephen Muggleton, S. Muggleton, 1995, New Generation Computing.

Complete Bottom-Up Predicate Invention in Meta-Interpretive Learning

Stephen Muggleton, Céline Hocquette, S. Muggleton, 2020, IJCAI.

PAC-learnability of determinate logic programs

Saso Dzeroski, Stephen Muggleton, Stuart J. Russell, 1992, COLT '92.

Learning Efficient Logical Robot Strategies Involving Composable Objects

Stephen Muggleton, Andrew Cropper, S. Muggleton, 2015, IJCAI.

Machine Learning for Systems Biology

Stephen Muggleton, S. Muggleton, 2005, ILP.

Using logic for protein structure prediction

Stephen Muggleton, Michael J. E. Sternberg, Robert King, 1992, Proceedings of the Twenty-Fifth Hawaii International Conference on System Sciences.

Proceedings of the 21st international conference on Inductive Logic Programming

Stephen Muggleton, Francesca A. Lisi, Alireza Tamaddoni-Nezhad, 2011, ILP 2011.

Automatic determination of protein fold signatures from structural superpositions

Stephen Muggleton, Michael J. E. Sternberg, A. P. Cootes, 2001, Electron. Trans. Artif. Intell..

Towards Efficient Higher-Order Logic Learning in a First-Order Datalog Framework

Stephen Muggleton, Niels Pahlavi, 2011, ILP.

Typed meta-interpretive learning for proof strategies

Alan Bundy, Stephen Muggleton, Andrew Cropper, 2015, ILP.

WIBL: Workbench for Integrative Biological Learning

Christopher J. Rawlings, Stephen Muggleton, Jan Taubert, 2011, J. Integr. Bioinform..

Selected Papers from the 6th International Workshop on Inductive Logic Programming

Stephen Muggleton, 1996 .

Carcinogenesis Predictions Using Inductive Logic Programming

Stephen Muggleton, Michael J. E. Sternberg, Ashwin Srinivasan, 1997 .

Learning optimal chess strategies

Stephen Muggleton, Michael Bain, S. Muggleton, 1994, Machine Intelligence 13.

Measuring Performance when Positives Are Rare: Relative Advantage versus Predictive Accuracy - A Biological Case Study

Ashwin Srinivasan, Stephen Muggleton, Christopher H. Bryant, 2000, ECML.

Probabilistic Inductive Logic Programming - Theory and Applications

Luc De Raedt, Kristian Kersting, Stephen Muggleton, 2008, Probabilistic Inductive Logic Programming.

The Application of Inductive Logic Programming to Finite Element Mesh Design

Stephen Muggleton, Bojan Dol, S. Muggleton, 2007 .

How Does Predicate Invention Affect Human Comprehensibility?

Stephen Muggleton, Ute Schmid, Alireza Tamaddoni-Nezhad, 2016, ILP.

Bayesian inductive logic programming

Stephen Muggleton, S. Muggleton, 1994, COLT '94.

Recent Developments in Applying Machine Learning to Drug Design

Stephen Muggleton, Michael J. E. Sternberg, Ashwin Srinivasan, 1998 .

Learning Large Margin First Order Decision Lists for Multi-Class Classification

Stephen Muggleton, Michael J. E. Sternberg, Huma Lodhi, 2009, Discovery Science.

Approaches and Applications of Inductive Programming (Dagstuhl Seminar 17382)

Stephen Muggleton, Rishabh Singh, Ute Schmid, 2017, Dagstuhl Reports.

Searching the Subsumption Lattice by a Genetic Algorithm

Stephen Muggleton, Alireza Tamaddoni-Nezhad, S. Muggleton, 2000, ILP.

Can HOLL Outperform FOLL?

Stephen Muggleton, Niels Pahlavi, 2010, ILP.

A Customisable Multiprocessor for Application-Optimised Inductive Logic Programming

Stephen Muggleton, Wayne Luk, Andreas Fidjeland, 2008, BCS Int. Acad. Conf..

Combining active learning with inductive logicprogramming to close the loop in machine learning

Stephen Muggleton, Christopher H. Bryant, Ch Bryant, 1999 .

Logical Vision: One-Shot Meta-Interpretive Learning from Real Images

Zhi-Hua Zhou, Stephen Muggleton, Alireza Tamaddoni-Nezhad, 2017, ILP.

Non-monotonic learning

Stephen Muggleton, Michael Bain, S. Muggleton, 1991 .

Turning 30: New Ideas in Inductive Logic Programming

Stephen Muggleton, Andrew Cropper, Sebastijan Dumancic, 2020, IJCAI.

Learning Stochastic Logical Automaton

Stephen Muggleton, Hiroaki Watanabe, S. Muggleton, 2006, JSAI Workshops.

An ILP System for Learning Head Output Connected Predicates

Stephen Muggleton, Alireza Tamaddoni-Nezhad, Jose Santos, 2009, EPIA.

Induction of Enzyme Classes from Biological Databases

Stephen Muggleton, Alireza Tamaddoni-Nezhad, Hiroaki Watanabe, 2003, ILP.

When Does It Pay Off to Use Sophisticated Entailment Engines in ILP?

Stephen Muggleton, Jose Santos, S. Muggleton, 2010, ILP.

Approaches and Applications of Inductive Programming (Dagstuhl Seminar 15442)

Stephen Muggleton, José Hernández-Orallo, Ute Schmid, 2015, Dagstuhl Reports.

Learning Stochastic Logic Programs

Stephen Muggleton, S. Muggleton, 2000, Electron. Trans. Artif. Intell..

An Experiment with Browsers that Learn

Stephen Muggleton, Rupert Parson, S. Muggleton, 1995, Machine Intelligence 15.

Application of machine learning to protein structure prediction and drug design

Stephen Muggleton, Jonathan D. Hirst, Michael J. E. Sternberg, 1994 .

Pharmacophore Discovery Using the Inductive Logic Programming System PROGOL

Ashwin Srinivasan, Stephen Muggleton, David Page, 1998, Machine Learning.

Structuring Knowledge by Asking Questions

Stephen Muggleton, S. Muggleton, 1987, EWSL.

Towards Chemical Universal Turing Machines

Stephen Muggleton, S. Muggleton, 2006, AAAI.

A Behavioral Comparison of Some Probabilistic Logic Models

Stephen Muggleton, Jianzhong Chen, S. Muggleton, 2008, Probabilistic Inductive Logic Programming.

Inductive Logic Programming - 21st International Conference, ILP 2011, Windsor Great Park, UK, July 31 - August 3, 2011, Revised Selected Papers

Stephen Muggleton, Francesca A. Lisi, Alireza Tamaddoni-Nezhad, 2012, ILP.

Learning Higher-Order Logic Programs through Abstraction and Invention

Stephen Muggleton, Andrew Cropper, S. Muggleton, 2016, IJCAI.

Learning probabilistic logic models from probabilistic examples

Stephen Muggleton, Jianzhong Chen, Jose Santos, 2007, Machine Learning.

Stochastic Refinement

Stephen Muggleton, Alireza Tamaddoni-Nezhad, S. Muggleton, 2010, ILP.

Abduction and induction for learning models of inhibition in metabolic networks

Stephen Muggleton, Antonis C. Kakas, Alireza Tamaddoni-Nezhad, 2005, Fourth International Conference on Machine Learning and Applications (ICMLA'05).

Guest Editors' Introduction

Stephen Muggleton, David Page, 2004, Machine Learning.

Bias reformulation for one-shot function induction

Stephen Muggleton, Joshua B. Tenenbaum, Eyal Dechter, 2014, ECAI.

The Effect of Relational Background Knowledge on Learning of Protein Three-Dimensional Fold Signatures

Stephen Muggleton, Michael J. E. Sternberg, Marcel Turcotte, 2001, Machine Learning.

An Experimental Comparison of Human and Machine Learning Formalisms

Stephen Muggleton, Donald Michie, Michael Bain, 1989, ML.

Relational Rule Induction with CProgol4.4: A Tutorial Introduction

Stephen Muggleton, John Firth, 2001 .

A Comparison of ILP and Propositional Systems on Propositional Traffic Data

Stephen Muggleton, Wim Van Laer, Jeremy Broughton, 1998, ILP.

Machine Invention of First Order Predicates by Inverting Resolution

Stephen Muggleton, Wray L. Buntine, S. Muggleton, 1988, ML.

Structured machine learning: the next ten years

Thomas G. Dietterich, Stephen Muggleton, Pedro M. Domingos, 2008, Machine Learning.

Elements of Computational Systems Biology: Lodhi/Computational Systems Biology

Stephen Muggleton, Huma Lodhi, 2010 .

Analogical Prediction

Stephen Muggleton, Michael Bain, S. Muggleton, 1999, ILP.

Variation of Background Knowledge in an Industrial Application of ILP

Stephen Muggleton, Michael J. E. Sternberg, Jan Taubert, 2010, ILP.

Multi-class protein fold recognition using large margin logic based divide and conquer learning

Stephen Muggleton, Michael J. E. Sternberg, Huma Lodhi, 2009, StReBio '09.

Semantics and derivation for Stochastic Logic Programs

Stephen Muggleton, 2000 .

Biochemical Knowledge Discovery Using Inductive Logic Programming

Ashwin Srinivasan, Stephen Muggleton, Ross D. King, 1998, Discovery Science.

Can predicate invention compensate for incomplete background knowledge?

Stephen Muggleton, Andrew Cropper, 2015, SCAI.

Duce, An Oracle-based Approach to Constructive Induction

Stephen Muggleton, S. Muggleton, 1987, IJCAI.

Probabilistic, Logical and Relational Learning - Towards a Synthesis, 30. January - 4. February 2005

Luc De Raedt, Thomas G. Dietterich, Stephen Muggleton, 2006, Probabilistic, Logical and Relational Learning.

Inductive logic programming

Stephen Muggleton, S. Muggleton, 1991, New Generation Computing.

Drug Design by Machine Learning

Ashwin Srinivasan, Stephen Muggleton, Ross D. King, 1995, Machine Intelligence 15.

Projection-Based PILP: Computational Learning Theory with Empirical Results

Stephen Muggleton, Hiroaki Watanabe, S. Muggleton, 2011, ILP.

Machine Learning of Biological Networks Using Abductive ILP

Stephen Muggleton, Alireza Tamaddoni-Nezhad, Hiroaki Watanabe, 2014 .

Interpretation of Hidden Node Methodology in Automated Classification of Neural Cell Morphology

Duncan Fyfe Gillies, Stephen Muggleton, Jung-Wook Bang, 2003, METMBS.

Machine intelligence 14: applied machine intelligence

Koichi Furukawa, Stephen Muggleton, Donald Michie, 1996 .

A Novel Logic-Based Approach for Quantitative Toxicology Prediction

Stephen Muggleton, Michael J. E. Sternberg, Huma Lodhi, 2007, J. Chem. Inf. Model..

Models of Inhibition in Biological Networks

Stephen Muggleton, Antonis C. Kakas, Alireza Tamaddoni-Nezhad, 2007 .

A Learnability Model for Universal Representations and Its Application to Top-down Induction of Decision Trees

Stephen Muggleton, David Page, 1995, Machine Intelligence 15.

Inductive logic programming: derivations, successes and shortcomings

Stephen Muggleton, S. Muggleton, 1993, SGAR.

The Scientific Contribution of Marek Sergot

Stephen Muggleton, Alessio Lomuscio, Antonis C. Kakas, 2012, Logic Programs, Norms and Action.

Can ILP Be Applied to Large Datasets?

Stephen Muggleton, Hiroaki Watanabe, S. Muggleton, 2009, ILP.

The Effect of Predicate Order on Curriculum Learning in ILP

Stephen Muggleton, Hank Conn, 2017, ILP.

Machine intelligence and inductive learning

Stephen Muggleton, 古川康一, Donald Michie, 1994 .

Protein secondary structure prediction using logic-based machine learning

Stephen Muggleton, Michael J. E. Sternberg, Robert King, 1992 .

How Much Can Experimental Cost Be Reduced in Active Learning of Agent Strategies?

Stephen Muggleton, Céline Hocquette, S. Muggleton, 2018, ILP.

Guest editorial: special issue on Inductive Logic Programming

Stephen Muggleton, Simon Colton, Ramón P. Otero, 2007, Machine Learning.

Inductive Logic Programming: Derivations, Successes and Shortcomings

Stephen Muggleton, 1993, ECML.

Latest Advances in Inductive Logic Programming

Stephen Muggleton, Hiroaki Watanabe, 2014 .

Inductive Logic Programming: 6th International Workshop, ILP-96, Stockholm, Sweden, August 26-28, 1996, Selected Papers

Stephen Muggleton, 1997 .

A Note on Refinement Operators for IE-Based ILP Systems

Stephen Muggleton, Alireza Tamaddoni-Nezhad, 2008, ILP.

ILP turns 20

Luc De Raedt, Katsumi Inoue, Ashwin Srinivasan, 2011, Machine Learning.

Efficient Induction of Logic Programs

Stephen Muggleton, Cao Feng, S. Muggleton, 1990, ALT.

Modelling Inhibition in Metabolic Pathways Through Abduction and Induction

Stephen Muggleton, Antonis C. Kakas, Alireza Tamaddoni-Nezhad, 2004, ILP.

Are Grammatical Representations Useful for Learning from Biological Sequence Data? - A Case Study

Ashwin Srinivasan, Christopher J. Rawlings, Stephen Muggleton, 2001, J. Comput. Biol..

14 CARCINOGENESIS PREDICTIONS

Stephen Muggleton, Michael J. E. Sternberg, Ashwin Srinivasan, 1997 .

Ultra-Strong Machine Learning: comprehensibility of programs learned with ILP

Stephen Muggleton, Ute Schmid, Alireza Tamaddoni-Nezhad, 2018, Machine Learning.

Carcinogenesis Predictions Using ILP

Ashwin Srinivasan, Stephen Muggleton, Ross D. King, 1997, ILP.

Generating Protein Three-dimensional Fold Signatures using Inductive Logic Programming

Stephen Muggleton, Michael J. E. Sternberg, Marcel Turcotte, 2001, Comput. Chem..

Wiley Series on Bioinformatics: Computational Techniques and Engineering

Stephen Muggleton, Huma Lodhi, 2010 .

Applied Machine intelligence

Stephen Muggleton, 古川康一, Donald Michie, 1995 .

Logical Vision: Meta-Interpretive Learning for Simple Geometrical Concepts

Zhi-Hua Zhou, Stephen Muggleton, Wang-Zhou Dai, 2015, ILP.

Logic and Learning: Turing's legacy

Stephen Muggleton, S. Muggleton, 1994, Machine Intelligence 13.

Machine learning metabolic pathway descriptions using a probabilistic relational representation

Stephen Muggleton, Nicos Angelopoulos, 2002 .

The Justification of Logical Theories based on Data Compression

Ashwin Srinivasan, Stephen Muggleton, Michael Bain, 1994, Machine Intelligence 13.

To the international computing community: A new East-West challenge

Stephen Muggleton, Donald Michie, David L. Page, 1994 .

Combining Inductive Logic Programming, Active Learning and Robotics to Discover the Function of Genes

Stephen Muggleton, Christopher H. Bryant, Douglas B. Kell, 2001, Electron. Trans. Artif. Intell..

Automatic Invention of Functional Abstractions

Stephen Muggleton, Robert J. Henderson, 2011, ILP.

Developing a Logical Model of Yeast Metabolism

Stephen Muggleton, Christopher H. Bryant, Douglas B. Kell, 2001, Electron. Trans. Artif. Intell..

Theories for Mutagenicity: A Study in First-Order and Feature-Based Induction

Ashwin Srinivasan, Stephen Muggleton, Ross D. King, 1996, Artif. Intell..

Automated identification of protein-ligand interaction features using Inductive Logic Programming: a hexose binding case study

Stephen Muggleton, David Page, Michael J. E. Sternberg, 2012, BMC Bioinformatics.

Inverting Entailment and Progol

Stephen Muggleton, 1993, Machine Intelligence 14.

Scaffold Hopping in Drug Discovery Using Inductive Logic Programming

Stephen Muggleton, Michael J. E. Sternberg, Ata Amini, 2008, J. Chem. Inf. Model..

QG/GA: a stochastic search for Progol

Stephen Muggleton, Alireza Tamaddoni-Nezhad, S. Muggleton, 2008, Machine Learning.

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

Stephen Muggleton, Alireza Tamaddoni-Nezhad, Dianhuan Lin, 2011, ILP.

A Genetic Algorithms Approach to ILP

Stephen Muggleton, Alireza Tamaddoni-Nezhad, S. Muggleton, 2002, ILP.

Abductive Stochastic Logic Programs for Metabolic Network Inhibition Learning

Stephen Muggleton, Jianzhong Chen, Jose Santos, 2007, MLG.

Support vector inductive logic programming outperforms the naive Bayes classifier and inductive logic programming for the classification of bioactive chemical compounds

Stephen Muggleton, Andreas Bender, Robert C. Glen, 2007, J. Comput. Aided Mol. Des..

MetaBayes: Bayesian Meta-Interpretative Learning Using Higher-Order Stochastic Refinement

Stephen Muggleton, Alireza Tamaddoni-Nezhad, Jianzhong Chen, 2013, ILP.

Compression, Significance, and Accuracy

Ashwin Srinivasan, Stephen Muggleton, Michael Bain, 1992, ML.

Meta-Interpretive Learning: Achievements and Challenges (Invited Paper)

Stephen Muggleton, S. Muggleton, 2017, RuleML+RR.

Support Vector Inductive Logic Programming

Stephen Muggleton, Michael J. E. Sternberg, Huma Lodhi, 2005, Discovery Science.

Repeat Learning Using Predicate Invention

Stephen Muggleton, Rupert Parson, Khalid Khan, 1998, ILP.

Logic-based machine learning

Stephen Muggleton, Flaviu Marginean, S. Muggleton, 2000 .

Inductive logic programming at 30 pdf

Stephen Muggleton, Andrew Cropper, Sebastijan Dumancic, 2021, Machine Learning.

Human-like Computer Vision

Stephen Muggleton, Wang-Zhou Dai, 2021, Human-Like Machine Intelligence.

Abductive Learning with Ground Knowledge Base

Stephen Muggleton, Wang-Zhou Dai, Yu-Feng Li, 2021, IJCAI.

Using Genetic Algorithms for learning clauses in first-order logic

Stephen Muggleton, Alireza Tamaddoni-Nezhad, S. Muggleton, 2001 .

Provided for Non-commercial Research and Educational Use Only. Not for Reproduction, Distribution or Commercial Use. Networking Agroecology: Integrating the Diversity of Agroecosystem Interactions

Stephen Muggleton, Alireza Tamaddoni-Nezhad, Nicolas Loeuille, 2022 .

Can ILP be Applied to Large Dataset ?

Stephen Muggleton, S. Muggleton, Hiroaki Watanabe, 2010 .

Declarative Kernels

Stephen Muggleton, Paolo Frasconi, Andrea Passerini, 2004 .

Automated Discovery of Food Webs from Ecological Data Using Logic-Based Machine Learning

Stephen Muggleton, Alireza Tamaddoni-Nezhad, David A. Bohan, 2011, PloS one.

Detecting Traac Problems with Ilp

Stephen Muggleton, Wim Van Laer, Martin Molina, 1998 .

Is Mutagenesis still challenging ?

Stephen Muggleton, Huma Lodhi, S. Muggleton, 2005 .

Networking Our Way to Better Ecosystem Service Provision.

Xin Zhou, Stephen Muggleton, Shanlin Liu, 2016, Trends in ecology & evolution.

Decision-Theoretic Logic Programs

Stephen Muggleton, S. Muggleton, Jianzhong Chen, 2009 .

Towards Belief Propagation in Shared Logic Program

Stephen Muggleton, Hiroaki Watanabe, .

Modeling the effects of toxins in metabolic networks.

Stephen Muggleton, Alireza Tamaddoni-Nezhad, Raphael A. G. Chaleil, 2007, IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society.

Abduction and induction for modelling inhibition in metabolic networks

Stephen Muggleton, Alireza Tamaddoni-Nezhad, Antonis Kakas, .