Descriptive Decision-making of Lung Cancer Treatment Using a DM Model with Dempster-Shafer Theory and Prospect Theory

被引：0

作者：

Nusrat, Elhum ^{[1
]}

Yamda, Koichi ^{[1
]}

机构：

[1] Nagaoka Univ Technol, Dept Management & Informat Syst Sci, 1603 1Kamitomioka, Nagaoka, Niigata 9402188, Japan

来源：

6TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND INTELLIGENT SYSTEMS, AND THE 13TH INTERNATIONAL SYMPOSIUM ON ADVANCED INTELLIGENT SYSTEMS | 2012年

关键词：

Dempster-Shafer Theory; Prospect theory; decision-making; uncertainty; lung cancer; decision attitude; BEHAVIORAL-MODELS; UNCERTAINTY; UTILITY; RISK;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper explains a descriptive decision-making framework under uncertainty elucidating different decision attitudes of a newly-diagnosed lung cancer patient regarding treatment decision. The problem of treatment decision making of a lung cancer patient has been defined as Evidential Decision-making Problem (EDMP) at first. Belief function of Dempster-Shafer theory is exploited to explain uncertainty of EDMP and Prospect theory is applied to accomplish a descriptive decision-making framework. The goal of this paper is to find what decisions regarding treatments are made by a lung cancer victim when attitudes towards uncertainty are different.

引用

页码：359 / 364

页数：6

共 25 条

[1] Loss aversion under prospect theory: A parameter-free measurement [J].