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Stephen Muggleton: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Stephen Muggleton, Cao Feng
    Efficient Induction of Logic Programs. [Citation Graph (4, 0)][DBLP]
    ALT, 1990, pp:368-381 [Conf]
  2. Stephen Muggleton, Wray L. Buntine
    Machine Invention of First Order Predicates by Inverting Resolution. [Citation Graph (1, 0)][DBLP]
    ML, 1988, pp:339-352 [Conf]
  3. Stephen Muggleton, Luc De Raedt
    Inductive Logic Programming: Theory and Methods. [Citation Graph (1, 0)][DBLP]
    J. Log. Program., 1994, v:19, n:, pp:629-679 [Journal]
  4. Stephen Muggleton
    Towards Chemical Universal Turing Machines. [Citation Graph (0, 0)][DBLP]
    AAAI, 2006, pp:- [Conf]
  5. Stephen Muggleton
    Inductive Logic Programming. [Citation Graph (0, 0)][DBLP]
    ALT, 1990, pp:42-62 [Conf]
  6. Stephen Muggleton
    Optimal Layered Learning: A PAC Approach to Incremental Sampling. [Citation Graph (0, 0)][DBLP]
    ALT, 1993, pp:37-44 [Conf]
  7. Stephen Muggleton, Donald Michie
    Machine Intelligibility and the Duality Principle. [Citation Graph (0, 0)][DBLP]
    Software Agents and Soft Computing, 1997, pp:276-292 [Conf]
  8. Huma Lodhi, Stephen Muggleton
    Modelling Metabolic Pathways Using Stochastic Logic Programs-Based Ensemble Methods. [Citation Graph (0, 0)][DBLP]
    CMSB, 2004, pp:119-133 [Conf]
  9. Saso Dzeroski, Stephen Muggleton, Stuart J. Russell
    PAC-Learnability of Determinate Logic Programs. [Citation Graph (0, 0)][DBLP]
    COLT, 1992, pp:128-135 [Conf]
  10. Stephen Muggleton
    Bayesian Inductive Logic Programming. [Citation Graph (0, 0)][DBLP]
    COLT, 1994, pp:3-11 [Conf]
  11. Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Stephen Muggleton
    05051 Executive Summary - Probabilistic, Logical and Relational Learning - Towards a Synthesis. [Citation Graph (0, 0)][DBLP]
    Probabilistic, Logical and Relational Learning, 2005, pp:- [Conf]
  12. Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Stephen Muggleton
    05051 Abstracts Collection - Probabilistic, Logical and Relational Learning - Towards a Synthesis. [Citation Graph (0, 0)][DBLP]
    Probabilistic, Logical and Relational Learning, 2005, pp:- [Conf]
  13. Stephen Muggleton
    Knowledge Discovery in Biological and Chemical Domains. [Citation Graph (0, 0)][DBLP]
    Discovery Science, 1998, pp:58-59 [Conf]
  14. Stephen Muggleton, Huma Lodhi, Ata Amini, Michael J. E. Sternberg
    Support Vector Inductive Logic Programming. [Citation Graph (0, 0)][DBLP]
    Discovery Science, 2005, pp:163-175 [Conf]
  15. Stephen Muggleton, Ashwin Srinivasan, Ross D. King, Michael J. E. Sternberg
    Biochemical Knowledge Discovery Using Inductive Logic Programming. [Citation Graph (0, 0)][DBLP]
    Discovery Science, 1998, pp:326-341 [Conf]
  16. Stephen Muggleton
    Inductive Logic Programming: Issues, Results and the LLL Challenge (abstract). [Citation Graph (0, 0)][DBLP]
    ECAI, 1998, pp:697- [Conf]
  17. Pavel Brazdil, Stephen Muggleton
    Learning to Relate Terms in a Multiple Agent Environment. [Citation Graph (0, 0)][DBLP]
    EWSL, 1991, pp:424-439 [Conf]
  18. Saso Dzeroski, Stephen Muggleton, Stuart J. Russell
    Learnability of Constrained Logic Programs. [Citation Graph (0, 0)][DBLP]
    ECML, 1993, pp:342-347 [Conf]
  19. Stephen Muggleton
    Structuring Knowledge by Asking Questions. [Citation Graph (0, 0)][DBLP]
    EWSL, 1987, pp:218-229 [Conf]
  20. Stephen Muggleton
    A Strategy for Constructing New Predicates in First-Order Logic. [Citation Graph (0, 0)][DBLP]
    EWSL, 1988, pp:123-130 [Conf]
  21. Stephen Muggleton
    Inductive Logic Programming: Derivations, Successes and Shortcomings. [Citation Graph (0, 0)][DBLP]
    ECML, 1993, pp:21-37 [Conf]
  22. Stephen Muggleton, Christopher H. Bryant, Ashwin Srinivasan
    Measuring Performance when Positives Are Rare: Relative Advantage versus Predictive Accuracy - A Biological Case Study. [Citation Graph (0, 0)][DBLP]
    ECML, 2000, pp:300-312 [Conf]
  23. Stephen Muggleton
    Developments in Inductive Logic Programming, Panel Position Paper. [Citation Graph (0, 0)][DBLP]
    FGCS, 1992, pp:1071-1073 [Conf]
  24. Ivan Bratko, Stephen Muggleton, Alen Varsek
    Learning Qualitative Models of Dynamic Systems. [Citation Graph (0, 0)][DBLP]
    ML, 1991, pp:385-388 [Conf]
  25. Cao Feng, Stephen Muggleton
    Towards Inductive Generalization in Higher Order Logic. [Citation Graph (0, 0)][DBLP]
    ML, 1992, pp:154-162 [Conf]
  26. Stephen Muggleton
    Bayesian Inductive Logic Programming. [Citation Graph (0, 0)][DBLP]
    ICML, 1994, pp:371-379 [Conf]
  27. Stephen Muggleton, Michael Bain, Jean Hayes Michie, Donald Michie
    An Experimental Comparison of Human and Machine Learning Formalisms. [Citation Graph (0, 0)][DBLP]
    ML, 1989, pp:113-118 [Conf]
  28. Stephen Muggleton, Christopher H. Bryant, Ashwin Srinivasan
    Learning Chomsky-like Grammars for Biological Sequence Families. [Citation Graph (0, 0)][DBLP]
    ICML, 2000, pp:631-638 [Conf]
  29. Stephen Muggleton, Ashwin Srinivasan, Michael Bain
    Compression, Significance, and Accuracy. [Citation Graph (0, 0)][DBLP]
    ML, 1992, pp:338-347 [Conf]
  30. Stephen Muggleton
    Duce, An Oracle-based Approach to Constructive Induction. [Citation Graph (0, 0)][DBLP]
    IJCAI, 1987, pp:287-292 [Conf]
  31. Stephen Muggleton
    Inductive Logic Programming: Inverse Resolution and Beyond. [Citation Graph (0, 0)][DBLP]
    IJCAI (1), 1995, pp:997- [Conf]
  32. Ashwin Srinivasan, Ross D. King, Stephen Muggleton, Michael J. E. Sternberg
    The Predictive Toxicology Evaluation Challenge. [Citation Graph (0, 0)][DBLP]
    IJCAI (1), 1997, pp:4-9 [Conf]
  33. Simon Colton, Stephen Muggleton
    ILP for Mathematical Discovery. [Citation Graph (0, 0)][DBLP]
    ILP, 2003, pp:93-111 [Conf]
  34. Saso Dzeroski, Nico Jacobs, Martín Molina, Carlos Moure, Stephen Muggleton, Wim Van Laer
    Detecting Traffic Problems with ILP. [Citation Graph (0, 0)][DBLP]
    ILP, 1998, pp:281-290 [Conf]
  35. Khalid Khan, Stephen Muggleton, Rupert Parson
    Repeat Learning Using Predicate Invention. [Citation Graph (0, 0)][DBLP]
    ILP, 1998, pp:165-174 [Conf]
  36. Stephen Moyle, Stephen Muggleton
    Learning Programs in the Event Calculus. [Citation Graph (0, 0)][DBLP]
    ILP, 1997, pp:205-212 [Conf]
  37. Stephen Muggleton
    Learning Structure and Parameters of Stochastic Logic Programs. [Citation Graph (0, 0)][DBLP]
    ILP, 2002, pp:198-206 [Conf]
  38. Stephen Muggleton
    Machine Learning for Systems Biology. [Citation Graph (0, 0)][DBLP]
    ILP, 2005, pp:416-423 [Conf]
  39. Stephen Muggleton
    Learning from Positive Data. [Citation Graph (0, 0)][DBLP]
    Inductive Logic Programming Workshop, 1996, pp:358-376 [Conf]
  40. Stephen Muggleton
    Advances in ILP Theory and Implementations (Abstract). [Citation Graph (0, 0)][DBLP]
    ILP, 1998, pp:9- [Conf]
  41. Stephen Muggleton
    Completing Inverse Entailment. [Citation Graph (0, 0)][DBLP]
    ILP, 1998, pp:245-249 [Conf]
  42. Stephen Muggleton, Christopher H. Bryant
    Theory Completion Using Inverse Entailment. [Citation Graph (0, 0)][DBLP]
    ILP, 2000, pp:130-146 [Conf]
  43. Stephen Muggleton, Michael Bain
    Analogical Prediction. [Citation Graph (0, 0)][DBLP]
    ILP, 1999, pp:234-244 [Conf]
  44. Stephen Muggleton, David Page, Ashwin Srinivasan
    An Initial Experiment into Stereochemistry-Based Drug Design Using Inductive Logic Programming. [Citation Graph (0, 0)][DBLP]
    Inductive Logic Programming Workshop, 1996, pp:25-40 [Conf]
  45. Ashwin Srinivasan, Ross D. King, Stephen Muggleton, Michael J. E. Sternberg
    Carcinogenesis Predictions Using ILP. [Citation Graph (0, 0)][DBLP]
    ILP, 1997, pp:273-287 [Conf]
  46. Stephen Muggleton, Alireza Tamaddoni-Nezhad, Hiroaki Watanabe
    Induction of Enzyme Classes from Biological Databases. [Citation Graph (0, 0)][DBLP]
    ILP, 2003, pp:269-280 [Conf]
  47. Alireza Tamaddoni-Nezhad, Antonis C. Kakas, Stephen Muggleton, Florencio Pazos
    Modelling Inhibition in Metabolic Pathways Through Abduction and Induction. [Citation Graph (0, 0)][DBLP]
    ILP, 2004, pp:305-322 [Conf]
  48. Alireza Tamaddoni-Nezhad, Stephen Muggleton
    Searching the Subsumption Lattice by a Genetic Algorithm. [Citation Graph (0, 0)][DBLP]
    ILP, 2000, pp:243-252 [Conf]
  49. Alireza Tamaddoni-Nezhad, Stephen Muggleton
    A Genetic Algorithms Approach to ILP. [Citation Graph (0, 0)][DBLP]
    ILP, 2002, pp:285-300 [Conf]
  50. Marcel Turcotte, Stephen Muggleton, Michael J. E. Sternberg
    Application of Inductive Logic Programming to Discover Rules Governing the Three-Dimensional Topology of Protein Structure. [Citation Graph (0, 0)][DBLP]
    ILP, 1998, pp:53-64 [Conf]
  51. Rupert Parson, Khalid Khan, Stephen Muggleton
    Theory Recovery. [Citation Graph (0, 0)][DBLP]
    ILP, 1999, pp:257-267 [Conf]
  52. Sam Roberts, Wim Van Laer, Nico Jacobs, Stephen Muggleton, Jeremy Broughton
    A Comparison of ILP and Propositional Systems on Propositional Traffic Data. [Citation Graph (0, 0)][DBLP]
    ILP, 1998, pp:291-299 [Conf]
  53. Hiroaki Watanabe, Stephen Muggleton
    Learning Stochastic Logical Automaton. [Citation Graph (0, 0)][DBLP]
    JSAI Workshops, 2005, pp:201-211 [Conf]
  54. Jung-Wook Bang, Alexandros Pappas, Duncan Fyfe Gillies, Stephen Muggleton
    Interpretation of Hidden Node Methodology in Automated Classification of Neural Cell Morphology. [Citation Graph (0, 0)][DBLP]
    METMBS, 2003, pp:527-532 [Conf]
  55. Michael Bain, Stephen Muggleton
    Learning optimal chess strategies. [Citation Graph (0, 0)][DBLP]
    Machine Intelligence 13, 1994, pp:291-309 [Conf]
  56. Stephen Muggleton
    Inverting Entailment and Progol. [Citation Graph (0, 0)][DBLP]
    Machine Intelligence 14, 1993, pp:135-190 [Conf]
  57. Stephen Muggleton
    Logic and Learning: Turing's legacy. [Citation Graph (0, 0)][DBLP]
    Machine Intelligence 13, 1994, pp:37-56 [Conf]
  58. Stephen Muggleton, David Page
    A Learnability Model for Universal Representations and Its Application to Top-down Induction of Decision Trees. [Citation Graph (0, 0)][DBLP]
    Machine Intelligence 15, 1995, pp:248-267 [Conf]
  59. Rupert Parson, Stephen Muggleton
    An Experiment with Browsers that Learn. [Citation Graph (0, 0)][DBLP]
    Machine Intelligence 15, 1995, pp:176-184 [Conf]
  60. Ashwin Srinivasan, Stephen Muggleton, Michael Bain
    The Justification of Logical Theories based on Data Compression. [Citation Graph (0, 0)][DBLP]
    Machine Intelligence 13, 1994, pp:87-121 [Conf]
  61. Michael J. E. Sternberg, Ross D. King, Ashwin Srinivasan, Stephen Muggleton
    Drug Design by Machine Learning. [Citation Graph (0, 0)][DBLP]
    Machine Intelligence 15, 1995, pp:328-338 [Conf]
  62. Michael J. E. Sternberg, R. A. Lewis, Ross D. King, Stephen Muggleton
    Machine Learning and biomolecular modelling. [Citation Graph (0, 0)][DBLP]
    Machine Intelligence 13, 1994, pp:193-212 [Conf]
  63. Huma Lodhi, Stephen Muggleton
    Computing Confidence Measures in Stochastic Logic Programs. [Citation Graph (0, 0)][DBLP]
    MICAI, 2005, pp:890-899 [Conf]
  64. Stephen Muggleton
    Inductive Logic Programming: Issues, Results and the Challenge of Learning Language in Logic. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 1999, v:114, n:1-2, pp:283-296 [Journal]
  65. Ashwin Srinivasan, Stephen Muggleton, Michael J. E. Sternberg, Ross D. King
    Theories for Mutagenicity: A Study in First-Order and Feature-Based Induction. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 1996, v:85, n:1-2, pp:277-299 [Journal]
  66. Ivan Bratko, Stephen Muggleton
    Applications of Inductive Logic Programming. [Citation Graph (0, 0)][DBLP]
    Commun. ACM, 1995, v:38, n:11, pp:65-70 [Journal]
  67. Stephen Muggleton
    Scientific Knowledge Discovery Using Inductive Logic Programming. [Citation Graph (0, 0)][DBLP]
    Commun. ACM, 1999, v:42, n:11, pp:42-46 [Journal]
  68. Marcel Turcotte, Stephen Muggleton, Michael J. E. Sternberg
    Generating Protein Three-dimensional Fold Signatures using Inductive Logic Programming. [Citation Graph (0, 0)][DBLP]
    Computers & Chemistry, 2002, v:26, n:1, pp:57-64 [Journal]
  69. 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. [Citation Graph (0, 0)][DBLP]
    Electron. Trans. Artif. Intell., 2001, v:5, n:B, pp:1-36 [Journal]
  70. A. P. Cootes, Stephen Muggleton, R. B. Greaves, Michael J. E. Sternberg
    Automatic determination of protein fold signatures from structural superpositions. [Citation Graph (0, 0)][DBLP]
    Electron. Trans. Artif. Intell., 2001, v:5, n:B, pp:245-274 [Journal]
  71. Stephen Muggleton
    Learning Stochastic Logic Programs. [Citation Graph (0, 0)][DBLP]
    Electron. Trans. Artif. Intell., 2000, v:4, n:B, pp:141-153 [Journal]
  72. 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. [Citation Graph (0, 0)][DBLP]
    Electron. Trans. Artif. Intell., 2001, v:5, n:B, pp:223-244 [Journal]
  73. Marcel Turcotte, Stephen Muggleton, Michael J. E. Sternberg
    Use of Inductive Logic Programming to Learn Principles of Protein Structure. [Citation Graph (0, 0)][DBLP]
    Electron. Trans. Artif. Intell., 2000, v:4, n:B, pp:119-124 [Journal]
  74. 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. [Citation Graph (0, 0)][DBLP]
    Journal of Computational Biology, 2001, v:8, n:5, pp:493-521 [Journal]
  75. Stephen Muggleton, David Page
    Guest Editors' Introduction: Inductive Logic Programming. [Citation Graph (0, 0)][DBLP]
    J. Log. Program., 1999, v:40, n:2-3, pp:125-126 [Journal]
  76. Paul W. Finn, Stephen Muggleton, David Page, Ashwin Srinivasan
    Pharmacophore Discovery Using the Inductive Logic Programming System PROGOL. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1998, v:30, n:2-3, pp:241-270 [Journal]
  77. Stephen Muggleton, David Page
    Guest Editors' Introduction. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1997, v:26, n:2-3, pp:97-98 [Journal]
  78. Alireza Tamaddoni-Nezhad, Raphael Chaleil, Antonis C. Kakas, Stephen Muggleton
    Application of abductive ILP to learning metabolic network inhibition from temporal data. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2006, v:64, n:1-3, pp:209-230 [Journal]
  79. Marcel Turcotte, Stephen Muggleton, Michael J. E. Sternberg
    The Effect of Relational Background Knowledge on Learning of Protein Three-Dimensional Fold Signatures. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2001, v:43, n:1/2, pp:81-95 [Journal]
  80. Simon Colton, Stephen Muggleton
    Mathematical applications of inductive logic programming. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2006, v:64, n:1-3, pp:25-64 [Journal]
  81. Stephen Muggleton
    Inductive Logic Programming. [Citation Graph (0, 0)][DBLP]
    New Generation Comput., 1991, v:8, n:4, pp:295-0 [Journal]
  82. Stephen Muggleton
    Inverse Entailment and Progol. [Citation Graph (0, 0)][DBLP]
    New Generation Comput., 1995, v:13, n:3&4, pp:245-286 [Journal]
  83. Stephen Muggleton, Fumio Mizoguchi, Koichi Furukawa
    Special Issue on Inductive Logic Programming. [Citation Graph (0, 0)][DBLP]
    New Generation Comput., 1995, v:13, n:3&4, pp:243-244 [Journal]
  84. Stephen Muggleton
    Inductive Logic Programming: Derivations, Successes and Shortcomings. [Citation Graph (0, 0)][DBLP]
    SIGART Bulletin, 1994, v:5, n:1, pp:5-11 [Journal]
  85. Stephen Muggleton, Alireza Tamaddoni-Nezhad
    QG/GA: A Stochastic Search for Progol. [Citation Graph (0, 0)][DBLP]
    ILP, 2006, pp:37-39 [Conf]
  86. Jianzhong Chen, Lawrence A. Kelley, Stephen Muggleton, Michael J. E. Sternberg
    Multi-class Prediction Using Stochastic Logic Programs. [Citation Graph (0, 0)][DBLP]
    ILP, 2006, pp:109-124 [Conf]
  87. Stephen Muggleton, Niels Pahlavi
    The Complexity of Translating BLPs to RMMs. [Citation Graph (0, 0)][DBLP]
    ILP, 2006, pp:351-365 [Conf]

  88. 07161 Abstracts Collection -- Probabilistic, Logical and Relational Learning - A Further Synthesis. [Citation Graph (, )][DBLP]


  89. Learning Large Margin First Order Decision Lists for Multi-Class Classification. [Citation Graph (, )][DBLP]


  90. An ILP System for Learning Head Output Connected Predicates. [Citation Graph (, )][DBLP]


  91. TopLog: ILP Using a Logic Program Declarative Bias. [Citation Graph (, )][DBLP]


  92. Subsumer: A Prolog theta-subsumption engine. [Citation Graph (, )][DBLP]


  93. Abduction and induction for learning models of inhibition in metabolic networks. [Citation Graph (, )][DBLP]


  94. Can ILP Be Applied to Large Datasets? [Citation Graph (, )][DBLP]


  95. A Behavioral Comparison of Some Probabilistic Logic Models. [Citation Graph (, )][DBLP]


  96. Protein Fold Discovery Using Stochastic Logic Programs. [Citation Graph (, )][DBLP]


  97. Learning Probabilistic Logic Models from Probabilistic Examples (Extended Abstract). [Citation Graph (, )][DBLP]


  98. A Note on Refinement Operators for IE-Based ILP Systems. [Citation Graph (, )][DBLP]


  99. Chess Revision: Acquiring the Rules of Chess Variants through FOL Theory Revision from Examples. [Citation Graph (, )][DBLP]


  100. ProGolem: A System Based on Relative Minimal Generalisation. [Citation Graph (, )][DBLP]


  101. Multi-class protein fold recognition using large margin logic based divide and conquer learning. [Citation Graph (, )][DBLP]


  102. Developing Robust Synthetic Biology Designs Using a Microfluidic Robot Scientist. [Citation Graph (, )][DBLP]


  103. From ILP to PILP. [Citation Graph (, )][DBLP]


  104. Abductive Stochastic Logic Programs for Metabolic Network Inhibition Learning. [Citation Graph (, )][DBLP]


  105. A Customisable Multiprocessor for Application-Optimised Inductive Logic Programming. [Citation Graph (, )][DBLP]


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