NDLI: An introduction to fuzzy answer set programming

Content Provider	Springer Nature Link
Author	Cock, Martine Vermeir, Dirk Nieuwenborgh, Davy
Copyright Year	2007
Abstract	In this paper we show how the concepts of answer set programming and fuzzy logic can be successfully combined into the single framework of fuzzy answer set programming (FASP). The framework offers the best of both worlds: from the answer set semantics, it inherits the truly declarative non-monotonic reasoning capabilities while, on the other hand, the notions from fuzzy logic in the framework allow it to step away from the sharp principles used in classical logic, e.g., that something is either completely true or completely false. As fuzzy logic gives the user great flexibility regarding the choice for the interpretation of the notions of negation, conjunction, disjunction and implication, the FASP framework is highly configurable and can, e.g., be tailored to any specific area of application. Finally, the presented framework turns out to be a proper extension of classical answer set programming, as we show, in contrast to other proposals in the literature, that there are only minor restrictions one has to demand on the fuzzy operations used, in order to be able to retrieve the classical semantics using FASP.
Ending Page	388
Page Count	26
Starting Page	363
File Format	PDF
ISSN	10122443
e-ISSN	15737470
Journal	Annals of Mathematics and Artificial Intelligence
Issue Number	3-4
Volume Number	50
Language	English
Publisher	Springer Netherlands
Publisher Date	2007-07-21
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Fuzzy logic Logic in artificial intelligence Answer set programming Knowledge representation Reasoning under uncertainty Computer Science Artificial Intelligence (incl. Robotics) Mathematics Complexity
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Artificial Intelligence

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