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Article type: Research Article
Authors: Jin, LeShenga; * | Chen, Zhen-Songb; * | Yager, Ronald R.c | Langari, Rezad
Affiliations: [a] Business School, Nanjing Normal University, Nanjing, China | [b] Department of Engineering Management, School of Civil Engineering, Wuhan University, Wuhan, China | [c] Machine Intelligence Institute, Iona College, New Rochelle, NY, USA | [d] Department of Mechanical Engineering, Texas A&M University, College StationUSA
Correspondence: [*] Corresponding authors. LeSheng Jin, Business School, Nanjing Normal University, Nanjing, China. E-mail: jls1980@163.com and Zhen-Song Chen, Department of Engineering Management, School of Civil Engineering, Wuhan University, Wuhan 430072, China. E-mail: zschen@whu.edu.cn.
Abstract: This letter reports a new type of uncertain information that is different from some well known existing uncertain information, such as probability information, fuzzy information, interval information and basic uncertain information. This type of uncertain information allows some specified compromise in interacting decision environments and gives some acceptance area when facing with uncertainties. We firstly introduce the cognitive interval information and then naturally propose the cognitive uncertain information as an extension. The featured acceptance area provides more flexibility in uncertain information handling and it can be regarded as some specified uncertain range (versus the certainty degree in basic uncertain information). The new proposals have advantages in some uncertain decision making scenarios where intersubjectivity and interaction of decision makers play important roles. Besides, some basic structural properties are briefly discussed. Moreover, some motivational examples are presented to show its usage in group decision making to help automatically obtain consistency or consensus in aggregating the different individual evaluations.
Keywords: Cognitive interval information, cognitive uncertain information, decision making, group decision making, information fusion, uncertain information
DOI: 10.3233/JIFS-223119
Journal: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 6, pp. 9411-9418, 2023
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