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Computational Logic: Logic Programming and Beyond pp 437–471Cite as

Learning in Clausal Logic: A Perspective on Inductive Logic Programming

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2407))

Abstract

Inductive logic programming is a form of machine learning from examples which employs the representation formalism of clausal logic. One of the earliest inductive logic programming systems was Ehud Shapiro’s Model Inference System [90], which could synthesise simple recursive programs like append/3. Many of the techniques devised by Shapiro, such as top-down search of program clauses by refinement operators, the use of intensional background knowledge, and the capability of inducing recursive clauses, are still in use today. On the other hand, significant advances have been made regarding dealing with noisy data, efficient heuristic and stochastic search methods, the use of logical representations going beyond definite clauses, and restricting the search space by means of declarative bias. The latter is a general term denoting any form of restrictions on the syntactic form of possible hypotheses. These include the use of types, input/output mode declarations, and clause schemata. Recently, some researchers have started using alternatives to Prolog featuring strong typing and real functions, which alleviate the need for some of the above ad-hoc mechanisms. Others have gone beyond Prolog by investigating learning tasks in which the hypotheses are not definite clause programs, but for instance sets of indefinite clauses or denials, constraint logic programs, or clauses representing association rules. The chapter gives an accessible introduction to the above topics. In addition, it outlines the main current research directions which have been strongly influenced by recent developments in data mining and challenging real-life applications.

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Authors and Affiliations

  1. University of Bristol, Woodland Road, Bristol, BS8 1UB, UK

    Peter Flach

  2. Jožef Stefan Institute, Jamova 39, 1000, Ljubljana, Slovenia

    Nada Lavrač

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  1. Peter Flach
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  1. Department of Computer Science, University of Cyprus, 75 Kallipoleos St., 1678, Nicosia, Cyprus

    Antonis C. Kakas

  2. Department of Computing, Imperial College of Science, Technology and Medicine, 180 Queen’s Gate, London, SW7 2BZ, UK

    Fariba Sadri

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Flach, P., Lavrač, N. (2002). Learning in Clausal Logic: A Perspective on Inductive Logic Programming. In: Kakas, A.C., Sadri, F. (eds) Computational Logic: Logic Programming and Beyond. Lecture Notes in Computer Science(), vol 2407. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45628-7_17

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