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Challenges for Inductive Logic Programming

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Progress in Artificial Intelligence (EPIA 1999)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1695))

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Abstract

Inductive logic programming (ILP) is a research area that has its roots in inductive machine learning and logic programming. Computational logic has significantly influenced machine learning through the field of inductive logic programming (ILP) which is concerned with the induction of logic programs from examples and background knowledge. Machine learning, and ILP in particular, has the potential to influence computational logic by providing an application area full of industrially significant problems, thus providing a challenge for other techniques in computational logic. In ILP, the recent shift of attention from program synthesis to knowledge discovery resulted in advanced techniques that are practically applicable for discovering knowledge in relational databases. This paper gives a brief introduction to ILP, presents state-of-the-art ILP techniques for relational knowledge discovery as well as some challegnes and directions for further developments in this area.

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Author information

Authors and Affiliations

  1. J. Stefan Institute, Jamova 39, 1000, Ljubljana, Slovenia

    Nada Lavrač

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  1. Nada Lavrač
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  1. Departamento de Informática, Universidade Nova de Lisboa, Quinta da Torre, P-2825-114, Caparica, Portugal

    Pedro Barahona

  2. Departamento de Matemática, Universidade de Évora, R. Romão Ramalho 59, P-7000, Évora, Portugal

    José J. Alferes

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Lavrač, N. (1999). Challenges for Inductive Logic Programming. In: Barahona, P., Alferes, J.J. (eds) Progress in Artificial Intelligence. EPIA 1999. Lecture Notes in Computer Science(), vol 1695. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48159-1_2

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  • DOI: https://doi.org/10.1007/3-540-48159-1_2

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