Abstract: Different from most sequential decisionmaking studies that focus on classical secretary problems, a decisionmaking method is constructed in this paper for a class of sequential decisionmaking problems, in which the object is unchanged but its state keeps updating in every stage. The method we propose is based on lens model and intuitionistic fuzzy set theory, which in details are: 1) using lens model for reference, the state in the next stage is predicted through the proximal information in current stage; 2) considering the uncertainty of the decisionmaking environment, intuitionistic fuzzy numbers are used to describe the information cues obtained by the decision-maker; 3) to better simulate the real decision-maker, the method is proposed in the framework of prospect theory. Based on above idea, two key parameters are invented for the method, named predicted "prospect" value and prediction performance, and specific decisionmaking steps are proposed. At last, a case in venture capital field is applied to illustrate the performance of the proposed method, where the data comes from analog simulation. Furthermore, comparative analysis of different occasion decision results and the robustness test are taken to verify the applicability and effectiveness of our method. Compared with the existing studies, the method we propose is more universal and can be applied to many scenes such as venture capital decisionmaking, emergency management and so on. Also, more research attention may be gathered in this field due to our study.

Key words: state update, sequential decision, lens model, intuitionistic fuzzy, prospect theory