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Inductive Programming

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Encyclopedia of Machine Learning and Data Mining

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Abstract

Inductive programming is introduced as a branch of program synthesis which is based on inductive inferece where recursive, declarative programs are constructed from incomplete specifications, especially from input/output examples. Inductive logic programming as well as 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 as well as inductive functional programming.

Most of the work by this author was done while on leave of absence in 2006/07 as a Visiting Faculty Member and Erasmus Exchange Teacher at Sabancı University, Turkey.

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Notes

  1. 1.

    •Online Platform of the Inductive Programming Community: http://www.inductive-programming.org/. •Journal of Automated Software Engineering, Special Issue on Inductive Programming, April 2001: Flener and Partridge (2001), http://user.it.uu.se/~pierref/ase/. •Biannual Workshops on Approaches and Applications of Inductive Programming: http://www.cogsys.wiai.uni-bamberg.de/aaip/. •Journal of Machine Learning Research, Special Topic on Approaches and Applications of Inductive Programming, February/March 2006: http://jmlr.csail.mit.edu/papers/topic/inductive_programming.html. •Dagstuhl Report 3/12 on Approaches and Applications of Inductive Programminghttp://drops.dagstuhl.de/opus/volltexte/2014/4507/.

Recommended Reading

•Online Platform of the Inductive Programming Community: http://www.inductive-programming.org/. •Journal of Automated Software Engineering, Special Issue on Inductive Programming, April 2001: Flener and Partridge (2001), http://user.it.uu.se/~pierref/ase/. •Biannual Workshops on Approaches and Applications of Inductive Programming: http://www.cogsys.wiai.uni-bamberg.de/aaip/. •Journal of Machine Learning Research, Special Topic on Approaches and Applications of Inductive Programming, February/March 2006: http://jmlr.csail.mit.edu/papers/topic/inductive_programming.html. •Dagstuhl Report 3/12 on Approaches and Applications of Inductive Programminghttp://drops.dagstuhl.de/opus/volltexte/2014/4507/.

  • Biermann AW (1978) The inference of regular LISP programs from examples. IEEE Trans Syst Man Cybern 8(8):585–600

    Article  MathSciNet  MATH  Google Scholar 

  • Flener P (1997) Inductive logic program synthesis with DIALOGS. In: Muggleton SH (ed) Revised selected papers of the 6th international workshop on inductive logic programming (ILP 1996), Stockholm. Volume 1314 of lecture notes in artificial intelligence. Springer, pp 175–198

    Google Scholar 

  • Flener P (2002) Achievements and prospects of program synthesis. In: Kakas A, Sadri F (eds) Computational logic: logic programming and beyond; essays in honour of Robert A. Kowalski. Volume 2407 of lecture notes in artificial intelligence. Springer, Berlin/New York, pp 310–346

    Google Scholar 

  • Flener P, Partridge D (2001) Inductive programming. Autom Softw Eng 8(2):131–137

    Article  Google Scholar 

  • Flener P, Yılmaz S (1999) Inductive synthesis of recursive logic programs: achievements and prospects. J Log Program 41(2–3):141–195

    Article  MathSciNet  MATH  Google Scholar 

  • Gulwani S, Kitzelmann E, Schmid U (2014) Approaches and Applications of Inductive Programming (Dagstuhl Seminar 13502). Dagstuhl Reports 3/12, Schloss Dagstuhl–Leibniz-Zentrum fuer Informatik, Dagstuhl

    Google Scholar 

  • Hofmann M, Kitzelmann E, Schmid U (2009) A unifying framework for analysis and evaluation of inductive programming systems. In: Goerzel B, Hitzler P, Hutter M (eds) Proceedings of the second conference on artificial general intelligence (AGI-09, Arlington, Virginia, 6–9 March 2009), Amsterdam. Atlantis Press, pp 55–60

    Google Scholar 

  • Katayama S (2005) Systematic search for lambda expressions. In: Trends in functional programming. Intellect, Bristol, pp 111–126

    Google Scholar 

  • Kitzelmann E, Schmid U (2006) Inductive synthesis of functional programs – an explanation based generalization approach. J Mach Learn Res 7(Feb): 429–454

    MathSciNet  MATH  Google Scholar 

  • Muggleton SH, Lin D (2013) Meta-interpretive learning of higher-order dyadic datalog: predicate invention revisited. In: Rossi F (ed) IJCAI 2013, proceedings of the 23rd international joint conference on artificial intelligence, Beijing, 3–9 Aug 2013. IJCAI/AAAI, pp 1551–1557

    Google Scholar 

  • Olsson JR (1995) Inductive functional programming using incremental program transformation. Artif Intell 74(1):55–83

    Article  Google Scholar 

  • Shapiro EY (1983) Algorithmic program debugging. The MIT Press, Cambridge

    MATH  Google Scholar 

  • Smith DR (1984) The synthesis of LISP programs from examples: a survey. In: Biermann AW, Guiho G, Kodratoff Y (eds) Automatic program construction techniques. Macmillan, New York, pp 307–324

    Google Scholar 

  • Smith DR (1985) Top-down synthesis of divide-and-conquer algorithms. Artificial Intelligence, 27(1):43–96

    Article  MathSciNet  MATH  Google Scholar 

  • Stahl I (1995) The appropriateness of predicate invention as bias shift operation in ILP. Mach Learn 20(1–2):95–117

    MATH  MathSciNet  Google Scholar 

  • Summers PD (1977) A methodology for LISP program construction from examples. J ACM 24(1): 161–175

    Article  MathSciNet  MATH  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Information Technology, Uppsala University, Box 337, SE – 751 05, Uppsala, Sweden

    Pierre Flener

  2. Faculty of Information Systems and Applied Computer Science, University of Bamberg, An der Weberei 5, DE – 96045, Bamberg, Germany

    Ute Schmid

Authors
  1. Pierre Flener
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  2. Ute Schmid
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Corresponding author

Correspondence to Pierre Flener .

Editor information

Editors and Affiliations

  1. The University of New South Wales, Sydney, NSW, Australia

    Claude Sammut

  2. Faculty of Information Technology, Monash University, Melbourne, VIC, Australia

    Geoffrey I. Webb

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Flener, P., Schmid, U. (2017). Inductive Programming. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning and Data Mining. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7687-1_137

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