Inductive logic programming: Difference between revisions

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'''Inductive logic programming''' ('''ILP''') is a subfield of [[symbolic artificial intelligence]] which uses [[logic programming]] as a uniform representation for examples, background knowledge and hypotheses. The term "''inductive''" here refers to [[Inductive reasoning|philosophical]] (i.e. suggesting a theory to explain observed facts) rather than [[mathematical induction|mathematical]] (i.e. proving a property for all members of a well-ordered set) induction. Given an encoding of the known background knowledge and a set of examples represented as a logical [[database]] of facts, an ILP system will derive a hypothesised logic program which [[Entailment|entails]] all the positive and none of the negative examples.

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* Visual example of inducing the grandparenthood relation by the [[#Implementations|Atom system]]. http://john-ahlgren.blogspot.com/2014/03/inductive-reasoning-visualized.html {{Webarchive|url=https://web.archive.org/web/20140326101408/http://john-ahlgren.blogspot.com/2014/03/inductive-reasoning-visualized.html |date=2014-03-26 }}

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[[Category:Inductive logic programming| ]]