A Review on Fuzzy Cognitive Map and Its Applications in Unmanned Systems

doi:10.12382/bgxb.2024.0804

Abstract

Abstract:

Fuzzy cognitive map (FCM),as a kind of knowledge graphical soft computing model with both fuzzy reasoning and neural network-like features,is highly compatible with the development direction of the third generation of artificial intelligence driven by both knowledge and data,and has been widely used in various fields.Firstly,the basic concepts and principles of FCM theory are introduced,the latest research progress and major existing problems of FCM are systematically analyzed from the three aspects of construction method,learning algorithm and extension model,and the main directions and key contents of the future research are summarized.Secondly,the application research of FCM in unmanned systems (single unmanned systems,multi-unmanned systems,unmanned-manned systems) are comprehensively reviewed and summarized.Finally,the key research contents and main research ideas of FCM in unmanned systems applications in the future are discussed in depth by analyzing in detail the technical requirements of single unmanned systems driven by autonomous intelligence,multi-unmanned systems driven by swarm intelligence,and unmanned-manned systems driven by mutual trust intelligence.

Key words: fuzzy cognitive map, artificial intelligence, knowledge-data-driven, unmanned systems

CLC Number:

TP18
E91

CHEN Jun, TONG Yan, NIU Yifeng, YU Hongbo, LI Ni, ZHANG Xinyu. A Review on Fuzzy Cognitive Map and Its Applications in Unmanned Systems[J]. Acta Armamentarii, 2025, 46(7): 240804-.

Figures/Tables 14

Fig.1 FCM papers published in the last 15 years

Fig.2 Main research content

Fig.3 Basic model of FCM

Fig.4 FCM model with memory

Fig.5 FCM model with delay

Fig.6 Knowledge-based approach for FCM construction

Fig.7 Data-based approach for FCM construction

Fig.8 Learning algorithms of FCM

Fig.9 Spectral map of FCM extensions

Fig.10 Classification diagram of FCM extensions

Fig.11 Unmanned systems and their intelligent technology fields

Fig.12 Applied research on single unmanned systems based on autonomous intelligence

Fig.13 Applied research on multi-unmanned systems based on swarm intelligence

Fig.14 Applied research on unmanned-manned systems based on mutual trust intelligence

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