310 research outputs found
The Logic of Counting Query Answers
We consider the problem of counting the number of answers to a first-order
formula on a finite structure. We present and study an extension of first-order
logic in which algorithms for this counting problem can be naturally and
conveniently expressed, in senses that are made precise and that are motivated
by the wish to understand tractable cases of the counting problem
Counting Complexity for Reasoning in Abstract Argumentation
In this paper, we consider counting and projected model counting of
extensions in abstract argumentation for various semantics. When asking for
projected counts we are interested in counting the number of extensions of a
given argumentation framework while multiple extensions that are identical when
restricted to the projected arguments count as only one projected extension. We
establish classical complexity results and parameterized complexity results
when the problems are parameterized by treewidth of the undirected
argumentation graph. To obtain upper bounds for counting projected extensions,
we introduce novel algorithms that exploit small treewidth of the undirected
argumentation graph of the input instance by dynamic programming (DP). Our
algorithms run in time double or triple exponential in the treewidth depending
on the considered semantics. Finally, we take the exponential time hypothesis
(ETH) into account and establish lower bounds of bounded treewidth algorithms
for counting extensions and projected extension.Comment: Extended version of a paper published at AAAI-1
Algorithms and Complexity Results for Persuasive Argumentation
The study of arguments as abstract entities and their interaction as
introduced by Dung (Artificial Intelligence 177, 1995) has become one of the
most active research branches within Artificial Intelligence and Reasoning. A
main issue for abstract argumentation systems is the selection of acceptable
sets of arguments. Value-based argumentation, as introduced by Bench-Capon (J.
Logic Comput. 13, 2003), extends Dung's framework. It takes into account the
relative strength of arguments with respect to some ranking representing an
audience: an argument is subjectively accepted if it is accepted with respect
to some audience, it is objectively accepted if it is accepted with respect to
all audiences. Deciding whether an argument is subjectively or objectively
accepted, respectively, are computationally intractable problems. In fact, the
problems remain intractable under structural restrictions that render the main
computational problems for non-value-based argumentation systems tractable. In
this paper we identify nontrivial classes of value-based argumentation systems
for which the acceptance problems are polynomial-time tractable. The classes
are defined by means of structural restrictions in terms of the underlying
graphical structure of the value-based system. Furthermore we show that the
acceptance problems are intractable for two classes of value-based systems that
where conjectured to be tractable by Dunne (Artificial Intelligence 171, 2007)
Exploiting chordal structure in polynomial ideals: a Gr\"obner bases approach
Chordal structure and bounded treewidth allow for efficient computation in
numerical linear algebra, graphical models, constraint satisfaction and many
other areas. In this paper, we begin the study of how to exploit chordal
structure in computational algebraic geometry, and in particular, for solving
polynomial systems. The structure of a system of polynomial equations can be
described in terms of a graph. By carefully exploiting the properties of this
graph (in particular, its chordal completions), more efficient algorithms can
be developed. To this end, we develop a new technique, which we refer to as
chordal elimination, that relies on elimination theory and Gr\"obner bases. By
maintaining graph structure throughout the process, chordal elimination can
outperform standard Gr\"obner basis algorithms in many cases. The reason is
that all computations are done on "smaller" rings, of size equal to the
treewidth of the graph. In particular, for a restricted class of ideals, the
computational complexity is linear in the number of variables. Chordal
structure arises in many relevant applications. We demonstrate the suitability
of our methods in examples from graph colorings, cryptography, sensor
localization and differential equations.Comment: 40 pages, 5 figure
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