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Inductive Programming

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Encyclopedia of Machine Learning and Data Science

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Abstract

Inductive programming is a branch of program synthesis that is based on inductive inference where a recursive, declarative program is constructed from an incomplete specification, especially from input–output examples. Inductive logic programming and inductive functional programming are addressed. Central concepts such as predicate invention and background knowledge are defined. Two worked-out examples are presented to illustrate inductive logic programming and inductive functional programming.

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Author information

Authors and Affiliations

  1. Department of Information Technology, Uppsala University, Uppsala, Sweden

    Pierre Flener

  2. Cognitive Systems, University of Bamberg, Bamberg, Germany

    Ute Schmid

Authors
  1. Pierre Flener
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  2. Ute Schmid
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Correspondence to Ute Schmid .

Editor information

Editors and Affiliations

  1. Clayton, VIC, Australia

    Dinh Phung

  2. Software Engineering, Monash University School of Computer Science &, Melbourne, VIC, Australia

    Geoffrey I. Webb

  3. Engineering (CSE), University of New South Wales School of Computer Science &, Sydney, NSW, Australia

    Claude Sammut

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Flener, P., Schmid, U. (2024). Inductive Programming. In: Phung, D., Webb, G.I., Sammut, C. (eds) Encyclopedia of Machine Learning and Data Science. Springer, New York, NY. https://doi.org/10.1007/978-1-4899-7502-7_137-2

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  • DOI: https://doi.org/10.1007/978-1-4899-7502-7_137-2

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4899-7502-7

  • Online ISBN: 978-1-4899-7502-7

  • eBook Packages: Springer Reference Computer SciencesReference Module Computer Science and Engineering

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Chapter history

  1. Latest

    Inductive Programming
    Published:
    19 December 2023

    DOI: https://doi.org/10.1007/978-1-4899-7502-7_137-2

  2. Original

    Inductive Programming
    Published:
    04 August 2016

    DOI: https://doi.org/10.1007/978-1-4899-7502-7_137-1

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