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Reducing fuzzy answer set programming to model finding in fuzzy logics

Jeroen Janssen UGent, Steven Schockaert UGent, Dirk Vermeir and Martine De Cock UGent (2012) THEORY AND PRACTICE OF LOGIC PROGRAMMING. 12. p.811-842
abstract
In recent years, answer set programming (ASP) has been extended to deal with multivalued predicates. The resulting formalisms allow for the modeling of continuous problems as elegantly as ASP allows for the modeling of discrete problems, by combining the stable model semantics underlying ASP with fuzzy logics. However, contrary to the case of classical ASP where many efficient solvers have been constructed, to date there is no efficient fuzzy ASP solver. A well-known technique for classical ASP consists of translating an ASP program P to a propositional theory whose models exactly correspond to the answer sets of P. In this paper, we show how this idea can be extended to fuzzy ASP, paving the way to implement efficient fuzzy ASP solvers that can take advantage of existing fuzzy logic reasoners.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
answer set programming, fuzzy logic, ASSAT, DEDUCTIVE DATABASES, EPISTEMIC FOUNDATION, SEMANTIC WEB, SAT SOLVERS, UNCERTAINTY, VAGUENESS, RETRIEVAL
journal title
THEORY AND PRACTICE OF LOGIC PROGRAMMING
Theory Pract. Log. Program.
volume
12
pages
811 - 842
Web of Science type
Article
Web of Science id
000310854200001
JCR category
LOGIC
JCR impact factor
0.288 (2012)
JCR rank
17/20 (2012)
JCR quartile
4 (2012)
ISSN
1471-0684
DOI
10.1017/S1471068411000093
language
English
UGent publication?
yes
classification
A1
copyright statement
I have transferred the copyright for this publication to the publisher
id
1938048
handle
http://hdl.handle.net/1854/LU-1938048
alternative location
http://arxiv.org/abs/1104.5133
date created
2011-10-28 17:48:26
date last changed
2013-07-15 11:32:22
@article{1938048,
  abstract     = {In recent years, answer set programming (ASP) has been extended to deal with multivalued predicates. The resulting formalisms allow for the modeling of continuous problems as elegantly as ASP allows for the modeling of discrete problems, by combining the stable model semantics underlying ASP with fuzzy logics. However, contrary to the case of classical ASP where many efficient solvers have been constructed, to date there is no efficient fuzzy ASP solver. A well-known technique for classical ASP consists of translating an ASP program P to a propositional theory whose models exactly correspond to the answer sets of P. In this paper, we show how this idea can be extended to fuzzy ASP, paving the way to implement efficient fuzzy ASP solvers that can take advantage of existing fuzzy logic reasoners.},
  author       = {Janssen, Jeroen and Schockaert, Steven and Vermeir, Dirk and De Cock, Martine},
  issn         = {1471-0684},
  journal      = {THEORY AND PRACTICE OF LOGIC PROGRAMMING},
  keyword      = {answer set programming,fuzzy logic,ASSAT,DEDUCTIVE DATABASES,EPISTEMIC FOUNDATION,SEMANTIC WEB,SAT SOLVERS,UNCERTAINTY,VAGUENESS,RETRIEVAL},
  language     = {eng},
  pages        = {811--842},
  title        = {Reducing fuzzy answer set programming to model finding in fuzzy logics},
  url          = {http://dx.doi.org/10.1017/S1471068411000093},
  volume       = {12},
  year         = {2012},
}

Chicago
Janssen, Jeroen, Steven Schockaert, Dirk Vermeir, and Martine De Cock. 2012. “Reducing Fuzzy Answer Set Programming to Model Finding in Fuzzy Logics.” Theory and Practice of Logic Programming 12: 811–842.
APA
Janssen, Jeroen, Schockaert, S., Vermeir, D., & De Cock, M. (2012). Reducing fuzzy answer set programming to model finding in fuzzy logics. THEORY AND PRACTICE OF LOGIC PROGRAMMING, 12, 811–842.
Vancouver
1.
Janssen J, Schockaert S, Vermeir D, De Cock M. Reducing fuzzy answer set programming to model finding in fuzzy logics. THEORY AND PRACTICE OF LOGIC PROGRAMMING. 2012;12:811–42.
MLA
Janssen, Jeroen, Steven Schockaert, Dirk Vermeir, et al. “Reducing Fuzzy Answer Set Programming to Model Finding in Fuzzy Logics.” THEORY AND PRACTICE OF LOGIC PROGRAMMING 12 (2012): 811–842. Print.