Details
Original language | English |
---|---|
Pages (from-to) | 617-640 |
Number of pages | 24 |
Journal | Cybernetics and systems |
Volume | 39 |
Issue number | 6 |
Publication status | Published - 12 Aug 2008 |
Abstract
Modern knowledge representation is a very dynamic domain because of continuous research and development. This paper presents Logical Petri Nets (LPNs) and Fuzzy Petri Nets (FPNs) as models for knowledge representation. It is shown that knowledge propagation, described using logical and fuzzy Petri nets, terminates in a unique stable state. Based on this result, the paper introduces an algorithm for knowledge propagation in decision support systems.
ASJC Scopus subject areas
- Computer Science(all)
- Software
- Computer Science(all)
- Information Systems
- Computer Science(all)
- Artificial Intelligence
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In: Cybernetics and systems, Vol. 39, No. 6, 12.08.2008, p. 617-640.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Decision support with logical and fuzzy Petri nets
AU - Lehocki, Fedor
AU - Juhas, Gabriel
AU - Lorenz, Robert
AU - Szczerbicka, Helena
AU - Drozda, Martin
N1 - Funding Information: The authors acknowledge the support from Ministry of Education of Slovak Republic for grants DAAD No. 07/2006, AV 4/0119/06, and AV 4/0103/06. The authors also acknowledge the support from the German Academic Exchange Service within the SAMANET project.
PY - 2008/8/12
Y1 - 2008/8/12
N2 - Modern knowledge representation is a very dynamic domain because of continuous research and development. This paper presents Logical Petri Nets (LPNs) and Fuzzy Petri Nets (FPNs) as models for knowledge representation. It is shown that knowledge propagation, described using logical and fuzzy Petri nets, terminates in a unique stable state. Based on this result, the paper introduces an algorithm for knowledge propagation in decision support systems.
AB - Modern knowledge representation is a very dynamic domain because of continuous research and development. This paper presents Logical Petri Nets (LPNs) and Fuzzy Petri Nets (FPNs) as models for knowledge representation. It is shown that knowledge propagation, described using logical and fuzzy Petri nets, terminates in a unique stable state. Based on this result, the paper introduces an algorithm for knowledge propagation in decision support systems.
UR - http://www.scopus.com/inward/record.url?scp=49549088581&partnerID=8YFLogxK
U2 - 10.1080/01969720802188235
DO - 10.1080/01969720802188235
M3 - Article
AN - SCOPUS:49549088581
VL - 39
SP - 617
EP - 640
JO - Cybernetics and systems
JF - Cybernetics and systems
SN - 0196-9722
IS - 6
ER -