Introduction
Fuzzy systems main asset over competing techniques has always been the capability to model expert qualitative knowledge. However, probably due to the limited scientific appeal, there has always been a scientific trend to disregard this simple but effective asset in favor of more hard-mathematical aspects of fuzzy systems. This can prove to be a mistake, especially when approaching qualitative real world dynamic systems, like, for instance, Social, Economical or Political Systems. Such systems are composed of a number of dynamic concepts or actors which are interrelated in complex ways usually including feedback links that propagate influences in complicated chains. Axelrod [1] introduced Cognitive Maps (CMs) as a way to represent and analyze the structure of those systems, but techniques that allow simulating the evolution of cognitive maps through time, what one could call Dynamic Cognitive Maps (DCM), were not available or had serious limitations during more than two decades [5], [9]. Fuzzy sets should have been regarded as the ideal “tool” when considering modeling such systems. However, proper qualitative modeling was consecutively disregarded even when fuzzy systems were used by Kosko to approach the problem (Fuzzy Cognitive Maps) [3], [4], [5], [11], [12], [13]. Rule Based Fuzzy Cognitive Maps (RB-FCM) were introduced has a qualitative technique to solve the limitations of previous approaches to this problem. They can be used as a tool by non-engineers and/or non-mathematicians since they eliminate the need for complex mathematical knowledge when modeling dynamic qualitative systems.
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References
Axelrod, R.: The Structure of Decision: Cognitive Maps of Political Elites. Princeton University Press, Princeton (1976)
Carvalho, J.P., Tomé, J.A.B.: Fuzzy Mechanisms for causal Relations. In: Proceedings of the IFSA 1999. 8th International Fuzzy systems Association World Congress, Taiwan (1999)
Carvalho, J.P., Tomé, J.A.B.: Rule Based Fuzzy Cognitive Maps – Fuzzy Causal Relations. In: Mohammadian, M. (ed.) Computational Intelligence for Modelling, Control and Automation: Evolutionary Computation & Fuzzy Logic for Intelligent Control, Knowledge Acquisition & Information Retrieval. IOS Press, Amsterdam (1999)
Carvalho, J.P., et al.: Issues on Dynamic Cognitive Map Modelling of Purse-seine Fishing Skippers Behavior. In: Zurada, J.M., Yen, G.G., Wang, J. (eds.) Computational Intelligence: Research Frontiers. LNCS, vol. 5050. Springer, Heidelberg (2008)
Carvalho, J.P.: Mapas Cognitivos Baseados em Regras Difusas: Modelação e Simulação da Dinâmica de Sistemas Qualitativos. Ph.D. thesis, Instituto Superior Técnico, Universidade Técnica de Lisboa, Portugal (2002)
Carvalho, J.P., Carola, M., Tomé, J.A.B.: Forest Fire Modelling using Rule-Based Fuzzy Cognitive Maps and Voronoi Based Cellular Automata. In: Proceedings of the 25th International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2006, Montreal, Canada (2006)
Carvalho, J.P., Tomé, J.A.B.: Interpolated Linguistic Terms. In: Proceedings of the 23rd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2004, Banff, Canada (2004)
Carvalho, J.P., Tomé, J.A.B.: Qualitative Modelling of an Economic System using Rule Based Fuzzy Cognitive Maps. In: FUZZ IEEE 2004 – IEEE International Conference on Fuzzy Systems, Budapest, Hungary (2004)
Carvalho, J.P., Tomé, J.A.B.: Rule Based Fuzzy Cognitive Maps and Fuzzy Cognitive Maps – A Comparative Study. In: Proceedings of the 18th International Conference of the North American Fuzzy Information Processing Society, NAFIPS 1999, New York (1999)
Carvalho, J.P., Tomé, J.A.B.: Using Interpolated Linguistic Term to Express Uncertainty in Rule Based Fuzzy Cognitive Maps. In: Proceedings of the 22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003, Chicago (2003)
Carvalho, J.P., Tomé, J.A.B.: Rule Based Fuzzy Cognitive Maps – Qualitative Systems Dynamics. In: Proceedings of the 19th International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2000, Atlanta (2000)
Carvalho, J.P., Tomé, J.A.B.: Issues on the Stability of Fuzzy Cognitive Maps and Rule-Based Fuzzy Cognitive Maps. In: Proceedings of the 21st International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2002, New Orleans (2002)
Carvalho, J.P., Tomé, J.A.B.: Rule Based Fuzzy Cognitive Maps – Expressing Time in Qualitative System Dynamics. In: Proceedings of the 2001 FUZZ-IEEE, Melbourne, Australia (2001)
Cossette, P., Audet, M.: Mapping of a Idiossincratic Schema. Journal of Management Studies 29(3), 325–347 (1992)
Eden, C.: Cognitive Mapping: a review. European Journal of Operational Research 36, 1–13 (1988)
Eden, C.: On the Nature of Cognitive Maps. Journal of Management Studies 29(3), 261–265 (1992)
Guimelli, C.: Transformation des Représentations sociales, Pratiques Nouvelles et Schèmes Cognitifs de Base. In: Guimelli, C. (ed.): Textes de Base en Sciences Sociales. TDB Delachaux et Niestlé (1993)
Huff, A.: Mapping Strategic Thought. John Wiley and Sons, Chichester (1990)
Kaufmann, A.: Introduction à la Théorie des Ensembles Floues, Aplications à la Linguistique, à la logique et à la sémantique. Masson (1975)
Klir, G., Folger, T.: Fuzzy Sets, Uncertainty and Information. Prentice-Hall, Englewood Cliffs (1988)
Kosko, B.: Fuzzy Thinking. Hyperion (1993)
Kosko, B.: Fuzzy Cognitive Maps. International Journal of Man-Machine Studies (1986)
Kosko, B.: Fuzzy Engineering. Prentice-Hall International Editions (1997)
Kosko, B.: Neural Networks and Fuzzy Systems: A Dynamical Systems Approach to Machine Intelligence. Prentice-Hall International Editions (1992)
Laukkanen, M.: Conducting Causal Mapping Research: Opportunities and Challenges. In: Eden, C., Spender, J.-C. (eds.) Managerial and Organisational Cognition. Sage, London (1998)
Laukkanen, M.: Comparative Cause Mapping of Management Cognition: A computer Database For Natural Data. Helsinki School of Economics and Business Publications (1992)
Pena, A., et al.: Predictive Causal Approach for Student Modeling, micai, Fifth Mexican International Conference on Artificial Intelligence, MICAI 2006 (2006), http://doi.ieeecomputersociety.org/10.1109/MICAI.2006.39
Spirtes, P., Glymour, C., Scheines, R.: Causation, Prediction and Search. The MIT Press, Cambridge (2000)
Zadeh, L.A.: Fuzzy Sets and Applications: Selected Papers. Wiley Interscience, Hoboken (1987)
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Carvalho, J.P., Tomé, J.A.B. (2009). Fuzzy Mechanisms for Qualitative Causal Relations. In: Seising, R. (eds) Views on Fuzzy Sets and Systems from Different Perspectives. Studies in Fuzziness and Soft Computing, vol 243. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-93802-6_19
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