Decomposition and Hierarchical Process for Fuzzy Cognitive Maps of Complex Systems

Abstract

of concepts and their relations. Concept (denoted by ver-In order to reduce the scale and complexity, the de-tex) can represent activity, cause, effect, intent, emotion, composition methods offuzzy cognitive maps for knowl-prone and trends of system. It reflects the attribute, peredge representation and reasoning are presented. Parti-formance, quality and state. Relations of concepts repretion the vertices of original cognitive map into some sent the relationship between concepts and effect relation groups, and then construct quotient cognitive map based (denoted by an arc with arrow, the direction of arrow on these groups. Thus, the analysis of the original FCM represents the direction of relationship and effect), its can be reduced to that of quotient FCM, which provides strength is represented by number value [']. global information oforiginal FCM, and some sub FCMs As a new technology method of knowledge reprewhich keep an original topological structure and infer-sentation and reasoning, the cognitive map of Axelord is ence and provide local information of original FCM. It a model to represent causal relation in representation and extremely reduces the original size and complexity, inference system, and provides an effective soft computmeanwhile, it is possible to study system at diferent ing tool to support self-adapted behavior based on translices and enhance the enrichment and flexibility of re-scendental knowledge. Cognitive map can represent dysearch between concepts. Some knowledge representa-namic causal system with feedback, which is difficult to tions and reasoning of complex system use the method of be represented by tree structure, Bayes network and hierarchicalforfuzzy cognitive maps. Therefore, it high-Markov. Recently, the theory of FCM has been found lights the hierarchical causal relationship and inclusion many applications in politics, economics, medicines, relationship between concepts, and embodies the space military, social relation and information system, network causal relation between concepts. administration, exception analysis, multi-agent system, industrial control and virtual reality etc[2'3]. Keywords: Complex system, fuzzy cognitive map, de-Now, we usually encounter large-scale and complicomposition, hierarchicalprocess. cated system in real-world applications. However, the study on very complicated, large-scale and multihierarchy FCMs is insufficient and many problems remain.

Research on the Influence of Artificial Intelligence on Economy and Society

“…From the theoretical level, the relevant literature directors studied the impact of AI on the future society [1] [2] [3], social development [4], social application [5] [6], employment [7], etc. Fuzzy cognitive map is applied to strategic planning, policy analysis and other fields because of its strong fuzzy information and causal relationship expression ability, simple reasoning and good explanatory ability [8]. In this paper, through the method of text mining and expert survey, we build a fuzzy cognitive map model of system element relationship, objectively analyze and study the impact of artificial intelligence on social system, hoping to provide some new ideas for related research, and provide reference for the government, enterprises, institutions and teenagers to meet the future challenges.…”