Answer set programming

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Abstract

Answer Set Programming (ASP) evolved from various fields such as Logic Programming, Deductive Databases, Knowledge Representation, and Nonmonotonic Reasoning, and serves as a flexible language for declarative problem solving. There are two main tasks in problem solving, representation and reasoning, which are clearly separated in the declarative paradigm. In ASP, representation is done using a rule-based language, while reasoning is performed using implementations of general-purpose algorithms, referred to as ASP solvers. Rules in ASP are interpreted according to common sense principles, including a variant of the closed-world-assumption (CWA) and the unique-name-assumption (UNA). Collections of ASP rules are referred to as ASP programs, which represent the modelled knowledge. To each ASP program a collection of answer sets, or intended models, is associated, which stand for the solutions to the modelled problem; this collection can also be empty, meaning that the modelled problem does not admit a solution. Several reasoning tasks exist: the classical ASP task is enumerating all answer sets or determining whether an answer set exists, but ASP also allows for query answering in brave or cautious modes. This article provides an introduction to the field, starting with historical perspectives, followed by a definition of the core language, a guideline to knowledge representation, an overview of existing ASP solvers, and a panorama of current research topics in the field. © 2013 Springer-Verlag.

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APA

Faber, W. (2013). Answer set programming. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8067 LNAI, pp. 162–193). https://doi.org/10.1007/978-3-642-39784-4_4

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