Inductive programming: Difference between revisions

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'''Inductive programming''' ('''IP''') is a special area of [[automatic programming]], covering research from [[artificial intelligence]] and [[Computer programming|programming]], which addresses [[machine learning|learning]] of typically [[declarative programming|declarative]] ([[logic programming|logic]] or [[functional programming|functional]]) and often [[recursion|recursive]] programs from incomplete specifications, such as input/output examples or constraints.

Depending on the programming language used, there are several kinds of inductive programming. [[Inductive functional programming]], which uses functional programming languages such as [[Lisp (programming language)|Lisp]] or [[Haskell (programming language)|Haskell]], and most especially [[inductive logic programming]], which uses logic programming languages such as [[Prolog]] and other logical representations such as [[description logics]], have been more prominent, but other (programming) language paradigms have also been used, such as [[constraint programming]] or [[probabilistic programming language|probabilistic programming]].

== Definition ==