Marked-Controlled Rewriting EFPN for Dynamic Knowledge Inference

GUŢULEAC, Emilian; MOCANU, Mihai

dc.contributor.author	GUŢULEAC, Emilian
dc.contributor.author	MOCANU, Mihai
dc.date.accessioned	2021-08-09T08:57:31Z
dc.date.available	2021-08-09T08:57:31Z
dc.date.issued	2008
dc.identifier.citation	GUTULEAC, Emilian, MOCANU, Mihai. Marked-Controlled Rewriting EFPN for Dynamic Knowledge Inference. In: dvances in Intelligent and Distributed Computing. Studies in Computational Intelligence, 2008, vol 78.p. 269-276. ISBN 978-3-540-74930-1.	en_US
dc.identifier.isbn	978-3-540-74930-1
dc.identifier.uri	https://doi.org/10.1007/978-3-540-74930-1_29
dc.identifier.uri	http://repository.utm.md/handle/5014/16676
dc.description	Access full text: https://doi.org/10.1007/978-3-540-74930-1_29	en_US
dc.description.abstract	In this paper, we introduce the descriptive marked-controlled rewriting Extended Fuzzy Petri Nets (EFPN) that can at run-time modify their own structure by rewriting some of their descriptive expression components where the enabling of a rule also depends on the net marking. They can then be used in the design of “dynamic knowledge inference” frameworks, which are adjustable according to knowledge variation as human cognition and thinking. This is very important for some domains, such as expert systems.	en_US
dc.language.iso	en	en_US
dc.publisher	Springer Nature Switzerland	en_US
dc.rights	Attribution-NonCommercial-NoDerivs 3.0 United States	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.subject	fuzzy Petri nets	en_US
dc.subject	Petri nets	en_US
dc.title	Marked-Controlled Rewriting EFPN for Dynamic Knowledge Inference	en_US
dc.type	Article	en_US