A logical reasoning based decision making method for handling qualitative knowledge

被引:6
|
作者
Chen, Shuwei [1 ]
Liu, Jun [2 ]
Xu, Yang [1 ]
机构
[1] Southwest Jiaotong Univ, Sch Math, Chengdu 610031, Sichuan, Peoples R China
[2] Ulster Univ, Sch Comp, Newtownabbey BT37 0QB, North Ireland
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
Decision making; Qualitative knowledge; Non-classical logic; Algebraic structure; Approximate reasoning; HEDGE ALGEBRAS; FUZZY-SETS; INFORMATION; MODEL; RANKING; WORDS; ALTERNATIVES; RESOLUTION;
D O I
10.1016/j.ijar.2020.11.003
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Successful decision-making analysis needs to take both advantages of human analysts and computers, and human knowledge is usually expressed in a qualitative way. Computer based approaches are good at handling quantitative data, while it is still challenging on how to well structure qualitative knowledge and incorporate them as part of decision analytics. This paper develops a logical reasoning based decision-making framework for handling qualitative human knowledge. In this framework, an algebraic structure is adopted for modelling qualitative human knowledge in a systematic way, and a logic based approximate reasoning method is then proposed for inferring the final decision based on the structured qualitative knowledge. By taking a non-classical logic as its formal foundation, the proposed logical reasoning based decision making method is able to model and infer with qualitative human knowledge directly without numerical approximation in a strict way. (C) 2020 Elsevier Inc. All rights reserved.
引用
收藏
页码:49 / 63
页数:15
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