131,992 research outputs found
Beliefs and Conflicts in a Real World Multiagent System
In a real world multiagent system, where the
agents are faced with partial, incomplete and
intrinsically dynamic knowledge, conflicts are
inevitable. Frequently, different agents have
goals or beliefs that cannot hold simultaneously.
Conflict resolution methodologies have to be
adopted to overcome such undesirable occurrences.
In this paper we investigate the application of
distributed belief revision techniques as the support
for conflict resolution in the analysis of the
validity of the candidate beams to be produced
in the CERN particle accelerators.
This CERN multiagent system contains a higher
hierarchy agent, the Specialist agent, which
makes use of meta-knowledge (on how the conflicting
beliefs have been produced by the other
agents) in order to detect which beliefs should be
abandoned. Upon solving a conflict, the Specialist
instructs the involved agents to revise their
beliefs accordingly.
Conflicts in the problem domain are mapped into
conflicting beliefs of the distributed belief revision
system, where they can be handled by
proven formal methods. This technique builds
on well established concepts and combines them
in a new way to solve important problems. We
find this approach generally applicable in several
domains
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
A Program-Level Approach to Revising Logic Programs under the Answer Set Semantics
An approach to the revision of logic programs under the answer set semantics
is presented. For programs P and Q, the goal is to determine the answer sets
that correspond to the revision of P by Q, denoted P * Q. A fundamental
principle of classical (AGM) revision, and the one that guides the approach
here, is the success postulate. In AGM revision, this stipulates that A is in K
* A. By analogy with the success postulate, for programs P and Q, this means
that the answer sets of Q will in some sense be contained in those of P * Q.
The essential idea is that for P * Q, a three-valued answer set for Q,
consisting of positive and negative literals, is first determined. The positive
literals constitute a regular answer set, while the negated literals make up a
minimal set of naf literals required to produce the answer set from Q. These
literals are propagated to the program P, along with those rules of Q that are
not decided by these literals. The approach differs from work in update logic
programs in two main respects. First, we ensure that the revising logic program
has higher priority, and so we satisfy the success postulate; second, for the
preference implicit in a revision P * Q, the program Q as a whole takes
precedence over P, unlike update logic programs, since answer sets of Q are
propagated to P. We show that a core group of the AGM postulates are satisfied,
as are the postulates that have been proposed for update logic programs
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