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Answer set programming (ASP) is a form of declarative programming oriented towards difficult (primarily NP-hard) search problems. It is based on the stable model (answer set) semantics of logic programming. In ASP, search problems are reduced to computing stable models, and ''answer set solvers'' — programs for generating stable models—are used to perform search. The computational process employed in the design of many answer set solvers is an enhancement of the DPLL algorithm and, in principle, it always terminates (unlike Prolog query evaluation, which may lead to an infinite loop). In a more general sense, ASP includes all applications of answer sets to knowledge representation〔 (as PDF )〕 and the use of Prolog-style query evaluation for solving problems arising in these applications. ==History== The planning method proposed in 1993 by Dimopoulos, Nebel and Köhler〔 (as Postscript )〕 is an early example of answer set programming. Their approach is based on the relationship between plans and stable models.〔 (as Postscript )〕 Soininen and Niemelä applied what is now known as answer set programming to the problem of product configuration. The use of answer set solvers for search was identified as a new programming paradigm by Marek and Truszczyński in a paper that appeared in a 25-year perspective on the logic programming paradigm published in 1999 〔 〕 and in (1999 ). Indeed, the new terminology of "answer set" instead of "stable model" was first proposed by Lifschitz〔 In 〕 in a paper appearing in the same retrospective volume as the Marek-Truszczynski paper. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Answer set programming」の詳細全文を読む スポンサード リンク
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