Answer Set Programming Modulo Acyclicity

IF 0.4 4区 计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING Fundamenta Informaticae Pub Date : 2015-09-27 DOI:10.3233/FI-2016-1398
J. Bomanson, M. Gebser, T. Janhunen, B. Kaufmann, Torsten Schaub
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引用次数: 32

Abstract

Acyclicity constraints are prevalent in knowledge representation and, in particular, applications where acyclic data structures such as DAGs and trees play a role. Recently, such constraints have been considered in the satisfiability modulo theories (SMT) framework, and in this paper we carry out an analogous extension to the answer set programming (ASP) paradigm. The resulting formalism, ASP modulo acyclicity, offers a rich set of primitives to express constraints related with recursive structures. The implementation, obtained as an extension to the state-of-the-art answer set solver clasp, provides a unique combination of traditional unfounded set checking with acyclicity propagation.
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答案集编程模非环性
非循环约束在知识表示中很普遍,特别是在dag和树等非循环数据结构发挥作用的应用程序中。最近,在可满足模理论(SMT)框架中考虑了这些约束,并在本文中对答案集规划(ASP)范式进行了类似的扩展。由此产生的形式化,ASP模非环性,提供了一组丰富的原语来表达与递归结构相关的约束。作为最先进的答案集求解器扣的扩展,该实现提供了传统无根据集检查与非循环传播的独特组合。
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来源期刊
Fundamenta Informaticae
Fundamenta Informaticae 工程技术-计算机:软件工程
CiteScore
2.00
自引率
0.00%
发文量
61
审稿时长
9.8 months
期刊介绍: Fundamenta Informaticae is an international journal publishing original research results in all areas of theoretical computer science. Papers are encouraged contributing: solutions by mathematical methods of problems emerging in computer science solutions of mathematical problems inspired by computer science. Topics of interest include (but are not restricted to): theory of computing, complexity theory, algorithms and data structures, computational aspects of combinatorics and graph theory, programming language theory, theoretical aspects of programming languages, computer-aided verification, computer science logic, database theory, logic programming, automated deduction, formal languages and automata theory, concurrency and distributed computing, cryptography and security, theoretical issues in artificial intelligence, machine learning, pattern recognition, algorithmic game theory, bioinformatics and computational biology, quantum computing, probabilistic methods, algebraic and categorical methods.
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