163 research outputs found
Two formalisms of extended possibilistic logic programming with context-dependent fuzzy unification A comparative description
AbstractPossibilistic logic is a logic of uncertainty where a certainty degree between 0 and 1, interpreted as a lower bound of a necessity measure, is attached to each classical formula. In this paper we present a comparative description of two models extending first order possibilistic logic so as to allow for fuzzy unification. The first formalism, called PLFC, is a general extension that allows clauses with fuzzy constants and fuzzily restricted quantifiers. The second formalism is an implication-based extension defined on top of Gödel infinitely-valued logic, capable of dealing with fuzzy constants. In this paper we compare these approaches, mainly their Horn-clause fragments, discussing their basic differences, specially in what regards their unification and automated deduction mechanisms
A logic programming framework for possibilistic argumentation: formalization and logical properties
In the last decade defeasible argumentation frameworks have evolved to become
a sound setting to formalize commonsense, qualitative reasoning. The logic programming
paradigm has shown to be particularly useful for developing different
argument-based frameworks on the basis of different variants of logic programming
which incorporate defeasible rules. Most of such frameworks, however, are unable to
deal with explicit uncertainty, nor with vague knowledge, as defeasibility is directly
encoded in the object language. This paper presents Possibilistic Logic Programming
(P-DeLP), a new logic programming language which combines features from
argumentation theory and logic programming, incorporating as well the treatment
of possibilistic uncertainty. Such features are formalized on the basis of PGL, a
possibilistic logic based on G¨odel fuzzy logic. One of the applications of P-DeLP
is providing an intelligent agent with non-monotonic, argumentative inference capabilities.
In this paper we also provide a better understanding of such capabilities
by defining two non-monotonic operators which model the expansion of a given
program P by adding new weighed facts associated with argument conclusions and
warranted literals, respectively. Different logical properties for the proposed operators
are studie
Weighted logics for artificial intelligence : an introductory discussion
International audienceBefore presenting the contents of the special issue, we propose a structured introductory overview of a landscape of the weighted logics (in a general sense) that can be found in the Artificial Intelligence literature, highlighting their fundamental differences and their application areas
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