16,081 research outputs found
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
Super Logic Programs
The Autoepistemic Logic of Knowledge and Belief (AELB) is a powerful
nonmonotic formalism introduced by Teodor Przymusinski in 1994. In this paper,
we specialize it to a class of theories called `super logic programs'. We argue
that these programs form a natural generalization of standard logic programs.
In particular, they allow disjunctions and default negation of arbibrary
positive objective formulas.
Our main results are two new and powerful characterizations of the static
semant ics of these programs, one syntactic, and one model-theoretic. The
syntactic fixed point characterization is much simpler than the fixed point
construction of the static semantics for arbitrary AELB theories. The
model-theoretic characterization via Kripke models allows one to construct
finite representations of the inherently infinite static expansions.
Both characterizations can be used as the basis of algorithms for query
answering under the static semantics. We describe a query-answering interpreter
for super programs which we developed based on the model-theoretic
characterization and which is available on the web.Comment: 47 pages, revised version of the paper submitted 10/200
A Goal-Directed Implementation of Query Answering for Hybrid MKNF Knowledge Bases
Ontologies and rules are usually loosely coupled in knowledge representation
formalisms. In fact, ontologies use open-world reasoning while the leading
semantics for rules use non-monotonic, closed-world reasoning. One exception is
the tightly-coupled framework of Minimal Knowledge and Negation as Failure
(MKNF), which allows statements about individuals to be jointly derived via
entailment from an ontology and inferences from rules. Nonetheless, the
practical usefulness of MKNF has not always been clear, although recent work
has formalized a general resolution-based method for querying MKNF when rules
are taken to have the well-founded semantics, and the ontology is modeled by a
general oracle. That work leaves open what algorithms should be used to relate
the entailments of the ontology and the inferences of rules. In this paper we
provide such algorithms, and describe the implementation of a query-driven
system, CDF-Rules, for hybrid knowledge bases combining both (non-monotonic)
rules under the well-founded semantics and a (monotonic) ontology, represented
by a CDF Type-1 (ALQ) theory. To appear in Theory and Practice of Logic
Programming (TPLP
A flexible framework for defeasible logics
Logics for knowledge representation suffer from over-specialization: while
each logic may provide an ideal representation formalism for some problems, it
is less than optimal for others. A solution to this problem is to choose from
several logics and, when necessary, combine the representations. In general,
such an approach results in a very difficult problem of combination. However,
if we can choose the logics from a uniform framework then the problem of
combining them is greatly simplified. In this paper, we develop such a
framework for defeasible logics. It supports all defeasible logics that satisfy
a strong negation principle. We use logic meta-programs as the basis for the
framework.Comment: Proceedings of 8th International Workshop on Non-Monotonic Reasoning,
April 9-11, 2000, Breckenridge, Colorad
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