13,694 research outputs found
Belief Revision in Structured Probabilistic Argumentation
In real-world applications, knowledge bases consisting of all the information
at hand for a specific domain, along with the current state of affairs, are
bound to contain contradictory data coming from different sources, as well as
data with varying degrees of uncertainty attached. Likewise, an important
aspect of the effort associated with maintaining knowledge bases is deciding
what information is no longer useful; pieces of information (such as
intelligence reports) may be outdated, may come from sources that have recently
been discovered to be of low quality, or abundant evidence may be available
that contradicts them. In this paper, we propose a probabilistic structured
argumentation framework that arises from the extension of Presumptive
Defeasible Logic Programming (PreDeLP) with probabilistic models, and argue
that this formalism is capable of addressing the basic issues of handling
contradictory and uncertain data. Then, to address the last issue, we focus on
the study of non-prioritized belief revision operations over probabilistic
PreDeLP programs. We propose a set of rationality postulates -- based on
well-known ones developed for classical knowledge bases -- that characterize
how such operations should behave, and study a class of operators along with
theoretical relationships with the proposed postulates, including a
representation theorem stating the equivalence between this class and the class
of operators characterized by the postulates
Abduction and Dialogical Proof in Argumentation and Logic Programming
We develop a model of abduction in abstract argumentation, where changes to
an argumentation framework act as hypotheses to explain the support of an
observation. We present dialogical proof theories for the main decision
problems (i.e., finding hypothe- ses that explain skeptical/credulous support)
and we show that our model can be instantiated on the basis of abductive logic
programs.Comment: Appears in the Proceedings of the 15th International Workshop on
Non-Monotonic Reasoning (NMR 2014
A Concurrent Language for Argumentation: Preliminary Notes
While agent-based modelling languages naturally implement concurrency, the currently available languages for argumentation do not allow to explicitly model this type of interaction. In this paper we introduce a concurrent language for handling process arguing and communicating using a shared argumentation framework (reminding shared constraint store as in concurrent constraint). We introduce also basic expansions, contraction and revision procedures as main bricks for enforcement, debate, negotiation and persuasion
The Complexity of Repairing, Adjusting, and Aggregating of Extensions in Abstract Argumentation
We study the computational complexity of problems that arise in abstract
argumentation in the context of dynamic argumentation, minimal change, and
aggregation. In particular, we consider the following problems where always an
argumentation framework F and a small positive integer k are given.
- The Repair problem asks whether a given set of arguments can be modified
into an extension by at most k elementary changes (i.e., the extension is of
distance k from the given set).
- The Adjust problem asks whether a given extension can be modified by at
most k elementary changes into an extension that contains a specified argument.
- The Center problem asks whether, given two extensions of distance k,
whether there is a "center" extension that is a distance at most (k-1) from
both given extensions.
We study these problems in the framework of parameterized complexity, and
take the distance k as the parameter. Our results covers several different
semantics, including admissible, complete, preferred, semi-stable and stable
semantics
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