Extended fuzzy cognitive maps

Author

Hagiwara, Masafumi

Author_Institution

Dept. of Psychol., Stanford Univ., CA, USA

fYear

1992

fDate

8-12 Mar 1992

Firstpage

795

Lastpage

801

Abstract

Fuzzy cognitive maps (FCMs) have been proposed to represent causal reasoning by using numeric processing. They graphically represent uncertain causal reasoning. In the resonant states, there emerges a limit cycle or a hidden pattern, which is a FCM inference. However, there are some shortcomings concerned with knowledge representation in the conventional FCMs. The author proposes extended fuzzy cognitive maps (E-FCMs) to represent causal relationships more naturally. The features of the E-FCMs are nonlinear membership functions, conditional weights, and time delay weights. Computer simulation results indicate the effectiveness of the E-FCMs

Keywords

cognitive systems; fuzzy logic; inference mechanisms; knowledge representation; uncertainty handling; causal reasoning; causal relationships; conditional weights; extended fuzzy cognitive maps; inference mechanisms; knowledge representation; nonlinear membership functions; numeric processing; time delay weights; uncertainty handling; Artificial intelligence; Computer simulation; Delay effects; Expert systems; Fuzzy cognitive maps; Knowledge representation; Learning; Limit-cycles; Psychology; Resonance;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 1992., IEEE International Conference on

Conference_Location

San Diego, CA

Print_ISBN

0-7803-0236-2

Type

conf

DOI

10.1109/FUZZY.1992.258761

Filename

258761