Transformation of Cognitive Maps
Cognitive maps (CMs), fuzzy cognitive maps (FCMs), and dynamical cognitive networks (DCNs) are related tools for modeling the cognition of human beings and facilitating machine inferences accordingly. FCMs extend CMs, and DCNs extend FCMs. Domain experts often face the challenge that CMs/FCMs are no...
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Published in | IEEE transactions on fuzzy systems Vol. 18; no. 1; pp. 114 - 124 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
New York
IEEE
01.02.2010
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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Abstract | Cognitive maps (CMs), fuzzy cognitive maps (FCMs), and dynamical cognitive networks (DCNs) are related tools for modeling the cognition of human beings and facilitating machine inferences accordingly. FCMs extend CMs, and DCNs extend FCMs. Domain experts often face the challenge that CMs/FCMs are not sufficiently capable in many applications and that DCNs are too complex. This paper presents a simplified DCN (sDCN) that extends the modeling capability of FCM/CM, yet maintains simplicity. Additionally, this paper proves that there exists a theoretical equivalence among models in the cognitive map family of CMs, FCMs, and sDCNs. It shows that every sDCN can be represented by an FCM or a CM, and vice versa ; similarly, every FCM can be represented by a CM, and vice versa . The result shows that CMs, FCMs, and sDCNs are a family of cognitive models that differs from many extended models. This paper also provides a constructive approach to transforming one cognitive map model into other cognitive map models in the family. Therefore, domain experts are able to model applications with more descriptive sDCNs and leave theoretical analysis to the simpler CM forms. The existence of theoretical transformation links among the models provides strong support for their theoretical analysis and flexibility in their applications. |
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AbstractList | Cognitive maps (CMs), fuzzy cognitive maps (FCMs), and dynamical cognitive networks (DCNs) are related tools for modeling the cognition of human beings and facilitating machine inferences accordingly. FCMs extend CMs, and DCNs extend FCMs. Domain experts often face the challenge that CMs/FCMs are not sufficiently capable in many applications and that DCNs are too complex. This paper presents a simplified DCN (sDCN) that extends the modeling capability of FCM/CM, yet maintains simplicity. Additionally, this paper proves that there exists a theoretical equivalence among models in the cognitive map family of CMs, FCMs, and sDCNs. It shows that every sDCN can be represented by an FCM or a CM, and vice versa; similarly, every FCM can be represented by a CM, and vice versa. The result shows that CMs, FCMs, and sDCNs are a family of cognitive models that differs from many extended models. This paper also provides a constructive approach to transforming one cognitive map model into other cognitive map models in the family. Therefore, domain experts are able to model applications with more descriptive sDCNs and leave theoretical analysis to the simpler CM forms. The existence of theoretical transformation links among the models provides strong support for their theoretical analysis and flexibility in their applications. |
Author | ZhiQi Shen ChunYan Miao ZhiQiang Liu Yuan Miao XueHong Tao |
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References | ref13 ref12 axelrod (ref1) 1976 ref15 miao (ref7) 2003; 5 ref11 ref10 ref2 ref17 ref16 ref19 ref18 huerga (ref26) 2002 papageorgiou (ref21) 2003; 2903 petalas (ref24) 2005; 1 ref23 ref25 ref20 ref22 ref28 ref27 ref29 gotoh (ref5) 1989 ref8 ref9 ref4 ref3 ref6 parenthoen (ref14) 2002; 3 |
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SubjectTerms | Australia Circuit analysis Cognition Cognitive models Collision mitigation Computer science education Control system synthesis Dynamical cognitive network (DCN) Ecosystems equivalence fuzzy cognitive map (FCM) Fuzzy cognitive maps Humans Multiagent systems Studies transformation |
Title | Transformation of Cognitive Maps |
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