4,919 research outputs found
Belief revision in the propositional closure of a qualitative algebra
Belief revision is an operation that aims at modifying old be-liefs so that
they become consistent with new ones. The issue of belief revision has been
studied in various formalisms, in particular, in qualitative algebras (QAs) in
which the result is a disjunction of belief bases that is not necessarily
repre-sentable in a QA. This motivates the study of belief revision in
formalisms extending QAs, namely, their propositional clo-sures: in such a
closure, the result of belief revision belongs to the formalism. Moreover, this
makes it possible to define a contraction operator thanks to the Harper
identity. Belief revision in the propositional closure of QAs is studied, an
al-gorithm for a family of revision operators is designed, and an open-source
implementation is made freely available on the web
Reason Maintenance - State of the Art
This paper describes state of the art in reason maintenance with a focus on its future usage in the KiWi project. To give a bigger picture of the field, it also mentions closely related issues such as non-monotonic logic and paraconsistency. The paper is organized as follows: first, two motivating scenarios referring to semantic wikis are presented which are then used to introduce the different reason maintenance techniques
A Rational and Efficient Algorithm for View Revision in Databases
The dynamics of belief and knowledge is one of the major components of any
autonomous system that should be able to incorporate new pieces of information.
In this paper, we argue that to apply rationality result of belief dynamics
theory to various practical problems, it should be generalized in two respects:
first of all, it should allow a certain part of belief to be declared as
immutable; and second, the belief state need not be deductively closed. Such a
generalization of belief dynamics, referred to as base dynamics, is presented,
along with the concept of a generalized revision algorithm for Horn knowledge
bases. We show that Horn knowledge base dynamics has interesting connection
with kernel change and abduction. Finally, we also show that both variants are
rational in the sense that they satisfy certain rationality postulates stemming
from philosophical works on belief dynamics
A New Rational Algorithm for View Updating in Relational Databases
The dynamics of belief and knowledge is one of the major components of any
autonomous system that should be able to incorporate new pieces of information.
In order to apply the rationality result of belief dynamics theory to various
practical problems, it should be generalized in two respects: first it should
allow a certain part of belief to be declared as immutable; and second, the
belief state need not be deductively closed. Such a generalization of belief
dynamics, referred to as base dynamics, is presented in this paper, along with
the concept of a generalized revision algorithm for knowledge bases (Horn or
Horn logic with stratified negation). We show that knowledge base dynamics has
an interesting connection with kernel change via hitting set and abduction. In
this paper, we show how techniques from disjunctive logic programming can be
used for efficient (deductive) database updates. The key idea is to transform
the given database together with the update request into a disjunctive
(datalog) logic program and apply disjunctive techniques (such as minimal model
reasoning) to solve the original update problem. The approach extends and
integrates standard techniques for efficient query answering and integrity
checking. The generation of a hitting set is carried out through a hyper
tableaux calculus and magic set that is focused on the goal of minimality.Comment: arXiv admin note: substantial text overlap with arXiv:1301.515
Algorithm for Adapting Cases Represented in a Tractable Description Logic
Case-based reasoning (CBR) based on description logics (DLs) has gained a lot
of attention lately. Adaptation is a basic task in the CBR inference that can
be modeled as the knowledge base revision problem and solved in propositional
logic. However, in DLs, it is still a challenge problem since existing revision
operators only work well for strictly restricted DLs of the \emph{DL-Lite}
family, and it is difficult to design a revision algorithm which is
syntax-independent and fine-grained. In this paper, we present a new method for
adaptation based on the DL . Following the idea of
adaptation as revision, we firstly extend the logical basis for describing
cases from propositional logic to the DL , and present a
formalism for adaptation based on . Then we present an
adaptation algorithm for this formalism and demonstrate that our algorithm is
syntax-independent and fine-grained. Our work provides a logical basis for
adaptation in CBR systems where cases and domain knowledge are described by the
tractable DL .Comment: 21 pages. ICCBR 201
Space-contained conflict revision, for geographic information
Using qualitative reasoning with geographic information, contrarily, for
instance, with robotics, looks not only fastidious (i.e.: encoding knowledge
Propositional Logics PL), but appears to be computational complex, and not
tractable at all, most of the time. However, knowledge fusion or revision, is a
common operation performed when users merge several different data sets in a
unique decision making process, without much support. Introducing logics would
be a great improvement, and we propose in this paper, means for deciding -a
priori- if one application can benefit from a complete revision, under only the
assumption of a conjecture that we name the "containment conjecture", which
limits the size of the minimal conflicts to revise. We demonstrate that this
conjecture brings us the interesting computational property of performing a
not-provable but global, revision, made of many local revisions, at a tractable
size. We illustrate this approach on an application.Comment: 14 page
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