Book chapter
A framework for fuzzy rule-based cognitive maps
PRICAI 2004: Trends in Artificial Intelligence. Volume 3157 Lecture Notes in Computer Science, Vol.3157, pp.454-463
Springer
2004
Abstract
Fuzzy Cognitive Maps (FCM), as defined originally, are limited in their capacity to model real-world scenarios, due to the rather simple representation of causal relationships between interrelated concepts. They can model a world that has only monotonic cause-effect relationships. Unlike this traditional FCM, which uses a linear function to represent the strength of relationship between two concepts, and a non-linear transfer function, to update the value of a concept during simulation, the FCM proposed by us uses fuzzy rules based on membership functions, and an aggregation operator respectively to serve these two purposes. This allows representation of non-monotonic causality, which is typical of many scenarios.
Details
- Title
- A framework for fuzzy rule-based cognitive maps
- Authors/Creators
- M.S. Khan (Author/Creator) - Murdoch UniversityS.W. Khor (Author/Creator) - Murdoch University
- Contributors
- C. Zhang (Editor)H.W. Guesgen (Editor)W-K Yeap (Editor)
- Publication Details
- PRICAI 2004: Trends in Artificial Intelligence. Volume 3157 Lecture Notes in Computer Science, Vol.3157, pp.454-463
- Publisher
- Springer
- Identifiers
- 991005544772807891
- Murdoch Affiliation
- School of Information Technology
- Language
- English
- Resource Type
- Book chapter
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