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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/11902

Title: Fuzzy Cognitive Maps for Modeling Complex
Authors: Leon, Maikel
Rodriguez, C.
Garcia, M.
Bello, Rafael
Vanhoof, Koen
Issue Date: 2010
Publisher: Springer
Citation: Advances in Artificial Intelligence: 9th Mexican International Conference on Artificial Intelligence, MICAI 2010, Pachuca, Mexico, November 8-13, 2010 Proceedings, Part I. p. 166-174.
Series/Report: Lecture Notes in Computer Science
Series/Report no.: 6437
Abstract: This paper presents Fuzzy Cognitive Maps as an approach in modeling the behavior and operation of complex systems. This technique is the fusion of the advances of the fuzzy logic and cognitive maps theories, they are fuzzy weighted directed graphs with feedback that create models that emulate the behavior of complex decision processes using fuzzy causal relations. There are some applications in diverse domains (manage, multiagent systems, etc.) and novel works (dynamical characteristics, learning procedures, etc.) to improve the performance of these systems. First the description and the methodology that this theory suggests is examined, also some ideas for using this approach in the control process area, and then the implementation of a tool based on Fuzzy Cognitive Maps is described. The application of this theory in the field of control and systems might contribute to the progress of more intelligent and independent control systems. Fuzzy Cognitive Maps have been fruitfully used in decision making and simulation of complex situation and analysis.
URI: http://hdl.handle.net/1942/11902
DOI: 10.1007/978-3-642-16761-4_15
ISBN: 978-3-642-16760-7
ISSN: 0302-9743
Category: C1
Type: Proceedings Paper
Validation: vabb, 2013
Appears in Collections: Research publications

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