A formulation of computational trust based on quantum decision theory

被引:8
作者
Ashtiani, Mehrdad [1 ]
Azgomi, Mohammad Abdollahi [1 ]
机构
[1] Iran Univ Sci & Technol, Sch Comp Engn, Trustworthy Comp Lab, Hengam St,Resalat Sq, Tehran 1684613114, Iran
基金
美国国家科学基金会;
关键词
Trust model; Quantum decision theory (QDT); Quantum interference; Attraction factors; Superposition axiom; Delegation; Order effect; INFORMATION; DISTRUST; DYNAMICS; MODEL;
D O I
10.1007/s10796-015-9555-4
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we propose a new formulation of computational trust based on quantum decision theory (QDT). By using this new formulation, we can divide the assigned trustworthiness values to objective and subjective parts. First, we create a mapping between the QDT definitions and the trustworthiness constructions. Then, we demonstrate that it is possible for the quantum interference terms to appear in the trust decision making process. By using the interference terms, we can quantify the emotions and subjective preferences of the trustor in various contexts with different amounts of uncertainty and risk. The non-commutative nature of quantum probabilities is a valuable mathematical tool to model the relative nature of trust. In relative trust models, the evaluation of a trustee candidate is not only dependent on the trustee itself, but on the other existing competitors. In other words, the first evaluation is performed in an isolated context whereas the rest of the evaluations are performed in a comparative one. It is shown that a QDT-based model of trust can account for these order effects in the trust decision making process. Finally, based on the principles of risk and uncertainty aversion, interference alternation theorem and interference quarter law, quantitative values are assigned to interference terms. By performing empirical evaluations, we have demonstrated that various scenarios can be better explained by a quantum model of trust rather than the commonly used classical models.
引用
收藏
页码:735 / 764
页数:30
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