The rapid development of science and technology brings the complexity and difficulty in decision-making. As a comprehensive tool for information expression, the probabilistic-based expressions can denote the complex information by considering the hesitancy and the accuracy at the same time. Because of the flexibility for expression, the related researches of the probabilistic-based expressions develop at a high rate of speed even though they are not systematical and mature enough. In this paper, we introduce the existing concepts of the probabilistic-based expressions and deeply analyze their developments and compare their similarities and differences. Each kind of concept has its own advantages and limitations, and can be applied for different decision-making environments. Besides, we investigate the research status of the techniques of the probabilistic-based expressions since they are the basis for most decision-making methods. For now, the existing decision-making methods for probabilistic-based expressions can be divided into the multi-attribute decision-making methods and the dynamic decision-making methods. It is worthy to point out that there are still a lot of severe challenges in the development process of probabilistic-based expressions, but their theoretical and applied value deserves to be paid much attention.
International Journal of Machine Learning and Cybernetics – Springer Journals
Published: May 31, 2018
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