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.
Bibliographical noteFunding Information:
This research has been partially supported by National Natural Science Foundation of China (Grant No. 61673320 , 61976130 ), the National Key R&D Program of China (Grant No. 2019YFB2101802 ), Sichuan Science and Technology Program (Grant No. 2020YJ0270 ), and Fundamental Research Funds for the Central Universities of China (Grant No. 2682018CX59 ).
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- Algebraic structure
- Approximate reasoning
- Decision making
- Non-classical logic
- Qualitative knowledge