Logic programming is a programming paradigm which is largely based on formal logic.
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Logic programming is a programming paradigm which is largely based on formal logic.
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Any program written in a logic programming language is a set of sentences in logical form, expressing facts and rules about some problem domain.
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An important concept in logic programming is the separation of programs into their logic component and their control component.
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Where "Logic programming" represents a logic program and "Control" represents different theorem-proving strategies.
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The inclusion of negation as failure means that logic programming is a kind of non-monotonic logic.
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In particular, Prakken and Sartor credit the representation of the British Nationality Act as a logic program with being "hugely influential for the development of computational representations of legislation, showing how logic programming enables intuitively appealing representations that can be directly deployed to generate automatic inferences".
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Abductive logic programming has been used for fault diagnosis, planning, natural language processing and machine learning.
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Metalogic programming allows object-level and metalevel representations to be combined, as in natural language.
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Metalogic is used in logic programming to implement metaprograms, which manipulate other programs, databases, knowledge bases or axiomatic theories as data.
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Constraint logic programming has been used to solve problems in such fields as civil engineering, mechanical engineering, digital circuit verification, automated timetabling, air traffic control, and finance.
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Arguably, concurrent logic programming is based on message passing, so it is subject to the same indeterminacy as other concurrent message-passing systems, such as Actors.
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Carl Hewitt has argued that concurrent logic programming is not based on logic in his sense that computational steps cannot be logically deduced.
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Inductive logic programming is concerned with generalizing positive and negative examples in the context of background knowledge: machine learning of logic programs.
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Some early designs of logic programming languages based on linear logic include LO, Lolli, ACL, and Forum.
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