Stephen Muggleton

José Carlos Almeida Santos, Houssam Nassif, David Page, Stephen H. Muggleton, Michael J. E. Sternberg: Automated identification of protein-ligand interaction features using Inductive Logic Programming: a hexose binding case study. BMC Bioinformatics 13: 162 (2012)

Stephen Muggleton, Luc De Raedt, David Poole, Ivan Bratko, Peter A. Flach, Katsumi Inoue, Ashwin Srinivasan: ILP turns 20 - Biography and future challenges. Machine Learning 86(1): 3-23 (2012)

Stephen Muggleton, Jianzhong Chen: Guest editorial: special issue on Inductive Logic Programming (ILP 2011). Machine Learning 89(3): 213-214 (2012)

Steve Barker, Andrew J. I. Jones, Antonis C. Kakas, Robert A. Kowalski, Alessio Lomuscio, Rob Miller, Stephen Muggleton, Giovanni Sartor: The Scientific Contribution of Marek Sergot. Logic Programs, Norms and Action 2012: 4-11

Ghazal Afroozi Milani, David Bohan, Stuart J. Dunbar, Stephen Muggleton, Alan Raybould, Alireza Tamaddoni-Nezhad: Machine Learning and Text Mining of Trophic Links. ICMLA (2) 2012: 410-415

Dianhuan Lin, Jianzhong Chen, Hiroaki Watanabe, Stephen Muggleton, Pooja Jain, Michael J. E. Sternberg, Charles Baxter, Richard A. Currie, Stuart J. Dunbar, Mark Earll, José Domingo Salazar: Does Multi-Clause Learning Help in Real-World Applications? ILP 2012: 221-237

Stephen H. Muggleton, Dianhuan Lin, Alireza Tamaddoni-Nezhad: MC-TopLog: Complete Multi-clause Learning Guided by a Top Theory. ILP 2012: 238-254

Alireza Tamaddoni-Nezhad, David Bohan, Alan Raybould, Stephen H. Muggleton: Machine Learning a Probabilistic Network of Ecological Interactions. ILP 2012: 332-346

Hiroaki Watanabe, Stephen H. Muggleton: Projection-Based PILP: Computational Learning Theory with Empirical Results. ILP 2012: 358-372

Stephen Muggleton, Alireza Tamaddoni-Nezhad, Francesca A. Lisi (Eds.): Inductive Logic Programming - 21st International Conference, ILP 2011, Windsor Great Park, UK, July 31 - August 3, 2011, Revised Selected Papers. Lecture Notes in Computer Science 7207, Springer 2012, isbn 978-3-642-31950-1

Victor Lesk, Jan Taubert, Christopher J. Rawlings, Stuart J. Dunbar, Stephen Muggleton: WIBL: Workbench for Integrative Biological Learning. J. Integrative Bioinformatics 8(2) (2011)

Jose Santos, Stephen Muggleton: Subsumer: A Prolog theta-subsumption engine. ICLP (Technical Communications) 2010: 172-181

Stephen Muggleton: Knowledge Mining Biological Network Models. Intelligent Information Processing 2010: 2

Stephen Muggleton, Jianzhong Chen, Hiroaki Watanabe, Stuart J. Dunbar, Charles Baxter, Richard A. Currie, José Domingo Salazar, Jan Taubert, Michael J. E. Sternberg: Variation of Background Knowledge in an Industrial Application of ILP. ILP 2010: 158-170

Niels Pahlavi, Stephen Muggleton: Can HOLL Outperform FOLL? ILP 2010: 198-205

Jose Santos, Stephen Muggleton: When Does It Pay Off to Use Sophisticated Entailment Engines in ILP? ILP 2010: 214-221

Alireza Tamaddoni-Nezhad, Stephen Muggleton: Stochastic Refinement. ILP 2010: 222-237

Alireza Tamaddoni-Nezhad, Stephen Muggleton: The lattice structure and refinement operators for the hypothesis space bounded by a bottom clause. Machine Learning 76(1): 37-72 (2009)

Huma Lodhi, Stephen Muggleton, Michael J. E. Sternberg: Multi-Class protein fold recognition using large margin logic based divide and conquer learning. SIGKDD Explorations 11(2): 117-122 (2009)

Huma Lodhi, Stephen Muggleton, Michael J. E. Sternberg: Learning Large Margin First Order Decision Lists for Multi-Class Classification. Discovery Science 2009: 168-183

José Carlos Almeida Santos, Alireza Tamaddoni-Nezhad, Stephen Muggleton: An ILP System for Learning Head Output Connected Predicates. EPIA 2009: 150-159

Stephen Muggleton, Aline Paes, Vítor Santos Costa, Gerson Zaverucha: Chess Revision: Acquiring the Rules of Chess Variants through FOL Theory Revision from Examples. ILP 2009: 123-130

Stephen Muggleton, José Carlos Almeida Santos, Alireza Tamaddoni-Nezhad: ProGolem: A System Based on Relative Minimal Generalisation. ILP 2009: 131-148

Hiroaki Watanabe, Stephen Muggleton: Can ILP Be Applied to Large Datasets? ILP 2009: 249-256

Huma Lodhi, Stephen Muggleton, Michael J. E. Sternberg: Multi-class protein fold recognition using large margin logic based divide and conquer learning. KDD Workshop on Statistical and Relational Learning in Bioinformatics 2009: 22-26

Stephen Muggleton, Ramón P. Otero, Simon Colton: Guest editorial: special issue on Inductive Logic Programming. Machine Learning 70(2-3): 119-120 (2008)

Stephen Muggleton, Alireza Tamaddoni-Nezhad: QG/GA: a stochastic search for Progol. Machine Learning 70(2-3): 121-133 (2008)

Thomas G. Dietterich, Pedro Domingos, Lise Getoor, Stephen Muggleton, Prasad Tadepalli: Structured machine learning: the next ten years. Machine Learning 73(1): 3-23 (2008)

Jianzhong Chen, Stephen Muggleton, José Carlos Almeida Santos: Learning probabilistic logic models from probabilistic examples. Machine Learning 73(1): 55-85 (2008)

Andreas Fidjeland, Wayne Luk, Stephen Muggleton: A Customisable Multiprocessor for Application-Optimised Inductive Logic Programming. BCS Int. Acad. Conf. 2008: 318-330

Stephen Muggleton, José Carlos Almeida Santos, Alireza Tamaddoni-Nezhad: TopLog: ILP Using a Logic Program Declarative Bias. ICLP 2008: 687-692

Jianzhong Chen, Lawrence A. Kelley, Stephen Muggleton, Michael J. E. Sternberg: Protein Fold Discovery Using Stochastic Logic Programs. Probabilistic Inductive Logic Programming 2008: 244-262

Alireza Tamaddoni-Nezhad, Stephen Muggleton: A Note on Refinement Operators for IE-Based ILP Systems. ILP 2008: 297-314

Stephen Muggleton, Jianzhong Chen: A Behavioral Comparison of Some Probabilistic Logic Models. Probabilistic Inductive Logic Programming 2008: 305-324

Stephen Muggleton: Developing Robust Synthetic Biology Designs Using a Microfluidic Robot Scientist. SBIA 2008: 4

Stephen Muggleton: From ILP to PILP. SBIA 2008: 7

Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Kristian Kersting, Stephen Muggleton (Eds.): Probabilistic, Logical and Relational Learning - A Further Synthesis, 15.04. - 20.04.2007. Dagstuhl Seminar Proceedings 07161, Internationales Begegnungs- und Forschungszentrum fuer Informatik (IBFI), Schloss Dagstuhl, Germany 2008

Luc De Raedt, Paolo Frasconi, Kristian Kersting, Stephen Muggleton (Eds.): Probabilistic Inductive Logic Programming - Theory and Applications. Lecture Notes in Computer Science 4911, Springer 2008, isbn 978-3-540-78651-1

Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Kristian Kersting, Stephen Muggleton: 07161 Abstracts Collection -- Probabilistic, Logical and Relational Learning - A Further Synthesis. Probabilistic, Logical and Relational Learning - A Further Synthesis 2007

Jianzhong Chen, Stephen Muggleton, Jose Santos: Learning Probabilistic Logic Models from Probabilistic Examples (Extended Abstract). ILP 2007: 22-23

Jianzhong Chen, Stephen Muggleton, Jose Santos: Abductive Stochastic Logic Programs for Metabolic Network Inhibition Learning. MLG 2007

Stephen Muggleton, Ramón P. Otero, Alireza Tamaddoni-Nezhad (Eds.): Inductive Logic Programming, 16th International Conference, ILP 2006, Santiago de Compostela, Spain, August 24-27, 2006, Revised Selected Papers. Lecture Notes in Computer Science 4455, Springer 2007, isbn 978-3-540-73846-6

Simon Colton, Stephen Muggleton: Mathematical applications of inductive logic programming. Machine Learning 64(1-3): 25-64 (2006)

Alireza Tamaddoni-Nezhad, Raphael Chaleil, Antonis C. Kakas, Stephen Muggleton: Application of abductive ILP to learning metabolic network inhibition from temporal data. Machine Learning 64(1-3): 209-230 (2006)

Stephen Muggleton: Towards Chemical Universal Turing Machines. AAAI 2006: 1527-1529

Stephen Muggleton, Alireza Tamaddoni-Nezhad: QG/GA: A Stochastic Search for Progol. ILP 2006: 37-39

Jianzhong Chen, Lawrence A. Kelley, Stephen Muggleton, Michael J. E. Sternberg: Multi-class Prediction Using Stochastic Logic Programs. ILP 2006: 109-124

Stephen Muggleton, Niels Pahlavi: The Complexity of Translating BLPs to RMMs. ILP 2006: 351-365

Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Stephen Muggleton (Eds.): Probabilistic, Logical and Relational Learning - Towards a Synthesis, 30. January - 4. February 2005. Dagstuhl Seminar Proceedings 05051, Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI), Schloss Dagstuhl, Germany 2006

Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Stephen Muggleton: 05051 Executive Summary - Probabilistic, Logical and Relational Learning - Towards a Synthesis. Probabilistic, Logical and Relational Learning 2005

Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Stephen Muggleton: 05051 Abstracts Collection - Probabilistic, Logical and Relational Learning - Towards a Synthesis. Probabilistic, Logical and Relational Learning 2005

Stephen Muggleton, Huma Lodhi, Ata Amini, Michael J. E. Sternberg: Support Vector Inductive Logic Programming. Discovery Science 2005: 163-175

Alireza Tamaddoni-Nezhad, Raphael Chaleil, Antonis C. Kakas, Stephen Muggleton: Abduction and induction for learning models of inhibition in metabolic networks. ICMLA 2005

Stephen Muggleton: Machine Learning for Systems Biology. ILP 2005: 416-423

Hiroaki Watanabe, Stephen Muggleton: Learning Stochastic Logical Automaton. JSAI Workshops 2005: 201-211

Huma Lodhi, Stephen Muggleton: Computing Confidence Measures in Stochastic Logic Programs. MICAI 2005: 890-899

Huma Lodhi, Stephen Muggleton: Modelling Metabolic Pathways Using Stochastic Logic Programs-Based Ensemble Methods. CMSB 2004: 119-133

Alireza Tamaddoni-Nezhad, Antonis C. Kakas, Stephen Muggleton, Florencio Pazos: Modelling Inhibition in Metabolic Pathways Through Abduction and Induction. ILP 2004: 305-322

Simon Colton, Stephen Muggleton: ILP for Mathematical Discovery. ILP 2003: 93-111

Stephen Muggleton, Alireza Tamaddoni-Nezhad, Hiroaki Watanabe: Induction of Enzyme Classes from Biological Databases. ILP 2003: 269-280

Jung-Wook Bang, Alexandros Pappas, Duncan Fyfe Gillies, Stephen Muggleton: Interpretation of Hidden Node Methodology in Automated Classification of Neural Cell Morphology. METMBS 2003: 527-532

Marcel Turcotte, Stephen Muggleton, Michael J. E. Sternberg: Generating Protein Three-dimensional Fold Signatures using Inductive Logic Programming. Computers & Chemistry 26(1): 57-64 (2002)

Andreas Fidjeland, Wayne Luk, Stephen Muggleton: Scalable acceleration of inductive logic programs. FPT 2002: 252-259

Stephen Muggleton: Learning Structure and Parameters of Stochastic Logic Programs. ILP 2002: 198-206

Alireza Tamaddoni-Nezhad, Stephen Muggleton: A Genetic Algorithms Approach to ILP. ILP 2002: 285-300

Christopher H. Bryant, Stephen Muggleton, Stephen G. Oliver, Douglas B. Kell, Philip G. K. Reiser, Ross D. King: Combining Inductive Logic Programming, Active Learning and Robotics to Discover the Function of Genes. Electron. Trans. Artif. Intell. 5(B): 1-36 (2001)

Philip G. K. Reiser, Ross D. King, Douglas B. Kell, Stephen Muggleton, Christopher H. Bryant, Stephen G. Oliver: Developing a Logical Model of Yeast Metabolism. Electron. Trans. Artif. Intell. 5(B): 223-244 (2001)

A. P. Cootes, Stephen Muggleton, R. B. Greaves, Michael J. E. Sternberg: Automatic determination of protein fold signatures from structural superpositions. Electron. Trans. Artif. Intell. 5(B): 245-274 (2001)

Stephen Muggleton, Christopher H. Bryant, Ashwin Srinivasan, Alex Whittaker, Simon Topp, Christopher J. Rawlings: Are Grammatical Representations Useful for Learning from Biological Sequence Data? - A Case Study. Journal of Computational Biology 8(5): 493-521 (2001)

Marcel Turcotte, Stephen Muggleton, Michael J. E. Sternberg: The Effect of Relational Background Knowledge on Learning of Protein Three-Dimensional Fold Signatures. Machine Learning 43(1/2): 81-95 (2001)

Marcel Turcotte, Stephen Muggleton, Michael J. E. Sternberg: Use of Inductive Logic Programming to Learn Principles of Protein Structure. Electron. Trans. Artif. Intell. 4(B): 119-124 (2000)

Stephen Muggleton: Learning Stochastic Logic Programs. Electron. Trans. Artif. Intell. 4(B): 141-153 (2000)

Stephen Muggleton, Christopher H. Bryant, Ashwin Srinivasan: Measuring Performance when Positives Are Rare: Relative Advantage versus Predictive Accuracy - A Biological Case Study. ECML 2000: 300-312

Stephen Muggleton, Christopher H. Bryant, Ashwin Srinivasan: Learning Chomsky-like Grammars for Biological Sequence Families. ICML 2000: 631-638

Stephen Muggleton, Christopher H. Bryant: Theory Completion Using Inverse Entailment. ILP 2000: 130-146

Alireza Tamaddoni-Nezhad, Stephen Muggleton: Searching the Subsumption Lattice by a Genetic Algorithm. ILP 2000: 243-252

Stephen Muggleton: Inductive Logic Programming: Issues, Results and the Challenge of Learning Language in Logic. Artif. Intell. 114(1-2): 283-296 (1999)

Stephen Muggleton: Scientific Knowledge Discovery Using Inductive Logic Programming. Commun. ACM 42(11): 42-46 (1999)

Stephen Muggleton, David Page: Guest Editors' Introduction: Inductive Logic Programming. J. Log. Program. 40(2-3): 125-126 (1999)

Stephen Muggleton, Michael Bain: Analogical Prediction. ILP 1999: 234-244

Rupert Parson, Khalid Khan, Stephen Muggleton: Theory Recovery. ILP 1999: 257-267

Koichi Furukawa, Donald Michie, Stephen Muggleton (Eds.): Machine Intelligence 15, Intelligent Agents [St. Catherine's College, Oxford, July 1995]. Oxford University Press 1999, isbn 0-19-853867-7

Paul W. Finn, Stephen Muggleton, David Page, Ashwin Srinivasan: Pharmacophore Discovery Using the Inductive Logic Programming System PROGOL. Machine Learning 30(2-3): 241-270 (1998)

Stephen Muggleton: Knowledge Discovery in Biological and Chemical Domains. Discovery Science 1998: 58-59

Stephen Muggleton, Ashwin Srinivasan, Ross D. King, Michael J. E. Sternberg: Biochemical Knowledge Discovery Using Inductive Logic Programming. Discovery Science 1998: 326-341

Stephen Muggleton: Inductive Logic Programming: Issues, Results and the LLL Challenge (abstract). ECAI 1998: 697

Stephen Muggleton: Advances in ILP Theory and Implementations (Abstract). ILP 1998: 9

Marcel Turcotte, Stephen Muggleton, Michael J. E. Sternberg: Application of Inductive Logic Programming to Discover Rules Governing the Three-Dimensional Topology of Protein Structure. ILP 1998: 53-64

Khalid Khan, Stephen Muggleton, Rupert Parson: Repeat Learning Using Predicate Invention. ILP 1998: 165-174

Stephen Muggleton: Completing Inverse Entailment. ILP 1998: 245-249

Saso Dzeroski, Nico Jacobs, Martín Molina, Carlos Moure, Stephen Muggleton, Wim Van Laer: Detecting Traffic Problems with ILP. ILP 1998: 281-290

Sam Roberts, Wim Van Laer, Nico Jacobs, Stephen Muggleton, Jeremy Broughton: A Comparison of ILP and Propositional Systems on Propositional Traffic Data. ILP 1998: 291-299

Stephen Muggleton, David Page: Guest Editors' Introduction. Machine Learning 26(2-3): 97-98 (1997)

Stephen Muggleton, Donald Michie: Machine Intelligibility and the Duality Principle. Software Agents and Soft Computing 1997: 276-292

Ashwin Srinivasan, Ross D. King, Stephen Muggleton, Michael J. E. Sternberg: The Predictive Toxicology Evaluation Challenge. IJCAI (1) 1997: 4-9

Stephen Moyle, Stephen Muggleton: Learning Programs in the Event Calculus. ILP 1997: 205-212

Ashwin Srinivasan, Ross D. King, Stephen Muggleton, Michael J. E. Sternberg: Carcinogenesis Predictions Using ILP. ILP 1997: 273-287

Stephen Muggleton (Ed.): Inductive Logic Programming, 6th International Workshop, ILP-96, Stockholm, Sweden, August 26-28, 1996, Selected Papers. Lecture Notes in Computer Science 1314, Springer 1997, isbn 3-540-63494-0

Ashwin Srinivasan, Stephen Muggleton, Michael J. E. Sternberg, Ross D. King: Theories for Mutagenicity: A Study in First-Order and Feature-Based Induction. Artif. Intell. 85(1-2): 277-299 (1996)

Stephen Muggleton, David Page, Ashwin Srinivasan: An Initial Experiment into Stereochemistry-Based Drug Design Using Inductive Logic Programming. Inductive Logic Programming Workshop 1996: 25-40

Stephen Muggleton: Learning from Positive Data. Inductive Logic Programming Workshop 1996: 358-376

Ivan Bratko, Stephen Muggleton: Applications of Inductive Logic Programming. Commun. ACM 38(11): 65-70 (1995)

Stephen Muggleton, Fumio Mizoguchi, Koichi Furukawa: Special Issue on Inductive Logic Programming. New Generation Comput. 13(3&4): 243-244 (1995)

Stephen Muggleton: Inverse Entailment and Progol. New Generation Comput. 13(3&4): 245-286 (1995)

Stephen Muggleton: Inductive Logic Programming: Inverse Resolution and Beyond. IJCAI (1) 1995: 997

Rupert Parson, Stephen Muggleton: An Experiment with Browsers that Learn. Machine Intelligence 15 1995: 176-184

Stephen Muggleton, David Page: A Learnability Model for Universal Representations and Its Application to Top-down Induction of Decision Trees. Machine Intelligence 15 1995: 248-267

Michael J. E. Sternberg, Ross D. King, Ashwin Srinivasan, Stephen Muggleton: Drug Design by Machine Learning. Machine Intelligence 15 1995: 328-338

Koichi Furukawa, Donald Michie, Stephen Muggleton (Eds.): Machine Intelligence 14, Proceedings of the Fourteenth Machine Intelligence Workshop, held at Hitachi Advanced Research Laboratories, Tokyo, Japan, November 1993. Oxford University Press 1995

Stephen Muggleton: Predicate invention and utilization. J. Exp. Theor. Artif. Intell. 6(1): 121-130 (1994)

Stephen Muggleton, Luc De Raedt: Inductive Logic Programming: Theory and Methods. J. Log. Program. 19/20: 629-679 (1994)

Stephen Muggleton: Inductive Logic Programming: Derivations, Successes and Shortcomings. SIGART Bulletin 5(1): 5-11 (1994)

Stephen Muggleton: Bayesian Inductive Logic Programming. COLT 1994: 3-11

Stephen Muggleton: Bayesian Inductive Logic Programming. ICML 1994: 371-379

Stephen Muggleton: Logic and Learning: Turing's legacy. Machine Intelligence 13 1994: 37-56

Ashwin Srinivasan, Stephen Muggleton, Michael Bain: The Justification of Logical Theories based on Data Compression. Machine Intelligence 13 1994: 87-121

Michael J. E. Sternberg, R. A. Lewis, Ross D. King, Stephen Muggleton: Machine Learning and biomolecular modelling. Machine Intelligence 13 1994: 193-212

Michael Bain, Stephen Muggleton: Learning optimal chess strategies. Machine Intelligence 13 1994: 291-309

Stephen Muggleton: Optimal Layered Learning: A PAC Approach to Incremental Sampling. ALT 1993: 37-44

Stephen Muggleton: Inductive Logic Programming: Derivations, Successes and Shortcomings. ECML 1993: 21-37

Saso Dzeroski, Stephen Muggleton, Stuart J. Russell: Learnability of Constrained Logic Programs. ECML 1993: 342-347

Stephen Muggleton: Inverting Entailment and Progol. Machine Intelligence 14 1993: 135-190

Saso Dzeroski, Stephen Muggleton, Stuart J. Russell: PAC-Learnability of Determinate Logic Programs. COLT 1992: 128-135

Stephen Muggleton: Developments in Inductive Logic Programming, Panel Position Paper. FGCS 1992: 1071-1073

Cao Feng, Stephen Muggleton: Towards Inductive Generalization in Higher Order Logic. ML 1992: 154-162

Stephen Muggleton, Ashwin Srinivasan, Michael Bain: Compression, Significance, and Accuracy. ML 1992: 338-347

Stephen Muggleton: Inductive Logic Programming. New Generation Comput. 8(4): 295-318 (1991)

Pavel Brazdil, Stephen Muggleton: Learning to Relate Terms in a Multiple Agent Environment. EWSL 1991: 424-439

Ivan Bratko, Stephen Muggleton, Alen Varsek: Learning Qualitative Models of Dynamic Systems. ML 1991: 385-388

Stephen Muggleton: Inductive acquisition of expert knowledge. Turing Institute Pr. 1990, isbn 978-0-201-17561-5, pp. I-XI, 1-220

Stephen Muggleton: Inductive Logic Programming. ALT 1990: 42-62

Stephen Muggleton, Cao Feng: Efficient Induction of Logic Programs. ALT 1990: 368-381

Stephen Muggleton, Michael Bain, Jean Hayes Michie, Donald Michie: An Experimental Comparison of Human and Machine Learning Formalisms. ML 1989: 113-118

Stephen Muggleton: A Strategy for Constructing New Predicates in First-Order Logic. EWSL 1988: 123-130

Stephen Muggleton, Wray L. Buntine: Machine Invention of First Order Predicates by Inverting Resolution. ML 1988: 339-352

Stephen Muggleton: Structuring Knowledge by Asking Questions. EWSL 1987: 218-229

Stephen Muggleton: Duce, An Oracle-based Approach to Constructive Induction. IJCAI 1987: 287-292