Muggleton, S. H.

See also:Structure-activity relationships derived by machine learning: the use of atoms and their bond connectivities to predict mutagenicity by inductive logic programming. PNAS, vol. 93 no. 1, pp. 438–442.Combining inductive logic programming, active learning and robotics to discover the function of genes. Electronic Transactions in Artificial Intelligence, 5 (B) , pp. 1-36.Support vector inductive logic programming outperforms the naive Bayes classifier and inductive logic programming for the classification of bioactive chemical compounds. Journal of Computer-Aided Molecular Design, May 2007, Volume 21, Issue 5, pp 269-280.Structure Activity Relationships (SAR) and Pharmacophore Discovery Using Inductive Logic Programming (ILP). QSAR & Combinatorial Science Volume 22, Issue 5, pp. 527–532, July 2003.Scaffold Hopping in Drug Discovery Using Inductive Logic Programming. J. Chem. Inf. Model., 2008, 48 (5), pp 949–957.Combining Active Learning with Inductive Logic Programming to close the loop in Machine Learning.A general approach for developing system-specific functions to score protein–ligand docked complexes using support vector inductive logic programming. Proteins: Structure, Function, and Bioinformatica: Special Issue: Third Meeting on the Critical Assessment of PRedicted Interactions, Volume 69, Issue 4, pages 823–831, December 2007.Discovering rules for protein–ligand specificity using support vector inductive logic programming. PEDS, Volume 22, Issue 9, pp. 561-567.New Generation Computing, 8, 295-318

Muggleton, S. H. | Feng, C.

A new research area, Inductive Logic Programming, is presently emerging. While inheriting various positive characteristics of the parent subjects of Logic Programming and Machine Learning, it is hoped that the new area will overcome many of the limitations of its forebears. Inductive Logic Programming needs to be based on sound principles from both Logic and Statistics. In terms of logic we provide a unifying framework for Muggleton and Buntine's Inverse Resolution (IR) and Plotkin's Relative Least General Generalisation (RLGG) by rederiving RLGG in terms of IR.

Muggleton, S. H. | Buntine, W.

Inductive logic programming is a new research area formed at the intersection of machine learning and logic programming. While the influence of logic programming has encouraged the development of strong theoretical foundations, this new area is inheriting its experimental orientation from machine learning. Inductive Logic Programming will be an invaluable text for all students of computer science, machine learning and logic programming at an advanced level.