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Title:
flp semantics without circular justifications for general logic programs
Author: Shen Yi-Dong ; Wang Kewen
Source: Proceedings of the National Conference on Artificial Intelligence
Conference Name: 26th AAAI Conference on Artificial Intelligence and the 24th Innovative Applications of Artificial Intelligence Conference, AAAI-12 / IAAI-12
Conference Date: July 22, 2012 - July 26, 2012
Issued Date: 2012
Conference Place: Toronto, ON, Canada
Keyword: Aggregates ; Artificial intelligence ; Data description ; Semantics
Indexed Type: EI
ISBN: 9781577355687
Department: (1) State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing 100190 China; (2) School of Computing and Information Technology Griffith University Brisbane QLD 4111 Australia
Sponsorship: Association for the Advancement of Artificial Intelligence (AAAI); AI Journal; Steven Kuhn, Pine River Capital; National Science Foundation; Microsoft Research
Abstract: The FLP semantics presented by (Faber, Leone, and Pfeifer 2004) has been widely used to define answer sets, called FLP answer sets, for different types of logic programs such as logic programs with aggregates, description logic programs (dl-programs), Hex programs, and logic programs with first-order formulas (general logic programs). However, it was recently observed that the FLP semantics may produce unintuitive answer sets with circular justifications caused by self-supporting loops. In this paper, we address the circular justification problem for general logic programs by enhancing the FLP semantics with a level mapping formalism. In particular, we extend the Gelfond-Lifschitz three step definition of the standard answer set semantics from normal logic programs to general logic programs and define for general logic programs the first FLP semantics that is free of circular justifications. We call this FLP semantics the well-justified FLP semantics. This method naturally extends to general logic programs with additional constraints like aggregates, thus providing a unifying framework for defining the well-justified FLP semantics for various types of logic programs. When this method is applied to normal logic programs with aggregates, the well-justified FLP semantics agrees with the conditional satisfaction based semantics defined by (Son, Pontelli, and Tu 2007); and when applied to dl-programs, the semantics agrees with the strongly well-supported semantics defined by (Shen 2011). Copyright © 2012, Association for the Advancement of Artificial Intelligence. All rights reserved.
English Abstract: The FLP semantics presented by (Faber, Leone, and Pfeifer 2004) has been widely used to define answer sets, called FLP answer sets, for different types of logic programs such as logic programs with aggregates, description logic programs (dl-programs), Hex programs, and logic programs with first-order formulas (general logic programs). However, it was recently observed that the FLP semantics may produce unintuitive answer sets with circular justifications caused by self-supporting loops. In this paper, we address the circular justification problem for general logic programs by enhancing the FLP semantics with a level mapping formalism. In particular, we extend the Gelfond-Lifschitz three step definition of the standard answer set semantics from normal logic programs to general logic programs and define for general logic programs the first FLP semantics that is free of circular justifications. We call this FLP semantics the well-justified FLP semantics. This method naturally extends to general logic programs with additional constraints like aggregates, thus providing a unifying framework for defining the well-justified FLP semantics for various types of logic programs. When this method is applied to normal logic programs with aggregates, the well-justified FLP semantics agrees with the conditional satisfaction based semantics defined by (Son, Pontelli, and Tu 2007); and when applied to dl-programs, the semantics agrees with the strongly well-supported semantics defined by (Shen 2011). Copyright © 2012, Association for the Advancement of Artificial Intelligence. All rights reserved.
Language: 英语
Content Type: 会议论文
URI: http://ir.iscas.ac.cn/handle/311060/15842
Appears in Collections:软件所图书馆_会议论文

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Recommended Citation:
Shen Yi-Dong,Wang Kewen. flp semantics without circular justifications for general logic programs[C]. 见:26th AAAI Conference on Artificial Intelligence and the 24th Innovative Applications of Artificial Intelligence Conference, AAAI-12 / IAAI-12. Toronto, ON, Canada. July 22, 2012 - July 26, 2012.
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