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AAAI 2017

Minimal Undefinedness for Fuzzy Answer Sets

Conference Paper AAAI Technical Track: Reasoning under Uncertainty Artificial Intelligence

Abstract

Fuzzy Answer Set Programming (FASP) combines the nonmonotonic reasoning typical of Answer Set Programming with the capability of Fuzzy Logic to deal with imprecise information and paraconsistent reasoning. In the context of paraconsistent reasoning, the fundamental principle of minimal undefinedness states that truth degrees close to 0 and 1 should be preferred to those close to 0. 5, to minimize the ambiguity of the scenario. The aim of this paper is to enforce such a principle in FASP through the minimization of a measure of undefinedness. Algorithms that minimize undefinedness of fuzzy answer sets are presented, and implemented.

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Context

Venue
AAAI Conference on Artificial Intelligence
Archive span
1980-2026
Indexed papers
28718
Paper id
20787507087342083
v2026.09.13