LiU Electronic Press
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Author:
Maluszynski, Jan (Linköping University, Department of Computer and Information Science, TCSLAB - Theoretical Computer Science Laboratory) (Linköping University, The Institute of Technology)
Szalas, Andrzej (Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab) (Linköping University, The Institute of Technology) (University of Warsaw, Poland )
Title:
Partiality and Inconsistency in Agents' Belief Bases
Department:
Linköping University, Department of Computer and Information Science, KPLAB - Knowledge Processing Lab
Linköping University, Department of Computer and Information Science, TCSLAB - Theoretical Computer Science Laboratory
Linköping University, The Institute of Technology
Publication type:
Conference paper (Refereed)
Language:
English
In:
Advanced Methods and Technologies for Agent and Multi-Agent Systems: Proceedings of the 7th KES Conference on Agent and Multi-Agent Systems - Technologies and Applications (KES-AMSTA 2013)
Editor:
Dariusz Barbucha, Manh Thanh Le, Robert J. Howlett, Lakhmi C. Jain
Conference:
7th KES Conference on Agent and Multi-Agent Systems - Technologies and Applications (KES-AMSTA 2013), 27-29 May 2013, Hue City, Vietnam
Publisher: IOS Press
Series:
Frontiers in Artificial Intelligence and Applications, ISSN 0922-6389 (print), 1879-8314 (online; 252
Pages:
3-17
Year of publ.:
2013
URI:
urn:nbn:se:liu:diva-107345
Permanent link:
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-107345
ISBN:
978-1-61499-253-0
ISI:
000339335600001
Subject category:
Computer Systems
Abstract(en) :

Agents' beliefs can be incomplete and partially inconsistent. The process of agents' belief formation in such contexts has to be supported by suitable tools allowing one to express a variety of inconsistency resolving and nonmonotonic reasoning techniques.

In this paper we discuss 4QL*, a general purpose rule-based query language allowing one to use rules with negation in the premises and in the conclusions of rules. It is based on a simple and intuitive semantics and provides uniform tools for lightweight versions of well-known forms of nonmonotonic reasoning. In addition, it is tractable w.r.t. data complexity and captures PTIME queries, so can be used in real-world applications.

Reasoning in 4QL* is based on well-supported models. We simplify and at the same time generalize previous definitions of well-supported models and develop a new algorithm for computing such models.

Available from:
2014-06-11
Created:
2014-06-11
Last updated:
2014-08-21
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