A Methodology for Developing Adaptive Fuzzy Cognitive Maps for Decision Support

M. Shamim Khan, Alex Chong, and Tom Gedeon

School of Information Technology, Murdoch University Perth, WA 6150, Australia

Received:

October 19, 2000

Accepted:

November 15, 2000

Published:

November 20, 2000

Keywords:

Cognitive map, Fuzzy Cognitive Map (FCM), Differential Hebbian Learning (DHL), Decision Support System (DSS)

Abstract

Differential Hebbian Learning (DHL) was proposed by Kosko as an unsupervised learning scheme for Fuzzy Cognitive Maps (FCMs). DHL can be used with a sequence of state vectors to adapt the causal link strengths of an FCM. However, it does not guarantee learning of the sequence by the FCM and no concrete procedures for the use of DHL has been developed. In this paper a formal methodology is proposed for using DHL in the development of FCMs in a decision support context. The four steps in the methodology are: (1) Creation of a crisp cognitive map; (2) Identification of event sequences for use in DHL; (3) Event sequence encoding using DHL; (4) Revision of the trained FCM. Feasibility of the proposed methodology is demonstrated with an example involving a dynamic system with feedback based on a real-life scenario.

Cite this article as:

M. Khan, A. Chong, and T. Gedeon, “A Methodology for Developing Adaptive Fuzzy Cognitive Maps for Decision Support,” J. Adv. Comput. Intell. Intell. Inform., Vol.4 No.6, pp. 403-407, 2000.

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