Authors:
Wladyslaw Homenda
1
;
Agnieszka Jastrzebska
1
and
Witold Pedrycz
2
Affiliations:
1
Warsaw University of Technology, Poland
;
2
Polish Academy of Sciences and University of Alberta, Poland
Keyword(s):
Fuzzy Cognitive Maps, Fuzzy Cognitive Map Reconstruction, Fuzzy Cognitive Map Exploration.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Cognitive Systems
;
Computational Intelligence
;
Enterprise Information Systems
;
Evolutionary Computing
;
Fuzzy Systems
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Knowledge Representation and Reasoning
;
Soft Computing
;
Symbolic Systems
;
Uncertainty in AI
Abstract:
The paper is focused on fuzzy cognitive maps - abstract soft computing models, which can be applied to model
complex systems with uncertainty. The authors present two distinct methodologies for fuzzy cognitive map
reconstruction based on gradient learning. Both theoretical and practical issues involved in the process of
a map reconstruction are discussed. Among researched and described aspects are: map sizes, data dimensionality,
distortions, optimization procedure, etc. Theoretical results are supported by a series of experiments,
that allow to evaluate the quality of the developed approach. The authors compare both procedures and discuss
practical issues, that are entailed in the developed methodology. The goal of this study is to investigate
theoretical and practical problems, that are relevant in the Fuzzy Cognitive Map reconstruction process.