A New Distance Function for Consensus Determination in Decision Support Systems

被引：1

作者：

Hernes, Marcin ^{[1
]}

Sobieska-Karpinska, Jadwiga ^{[2
]}

Kozierkiewicz, Adrianna ^{[3
]}

Pietranik, Marcin ^{[3
]}

机构：

[1] Wroclaw Univ Econ, Ul Komandorska 118-120, PL-53345 Wroclaw, Poland

[2] Witelon State Univ Appl Sci Legnica, Ul Sejmowa 5A, PL-59220 Legnica, Poland

[3] Wroclaw Univ Technol, Wybrzeze Wyspianskiego 27, PL-50370 Wroclaw, Poland

来源：

COMPUTATIONAL COLLECTIVE INTELLIGENCE, ICCCI 2018, PT II | 2018年 / 11056卷

关键词：

Knowledge conflicts; Consensus methods; Decision support systems; Distance functions;

D O I：

10.1007/978-3-319-98446-9_15

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Consensus methods are used mainly to solve conflicts of knowledge in decision support systems. Generally speaking, conflicts of knowledge arise from the fact that system nodes (for example, agents, experts) may present various decisions or solutions to the user. This may be due to the use of various methods of decision support or different information sources by agents/experts. If there is a conflict of knowledge in the system and they are not automatically resolving the system cannot generate the final decision, and hence - the decision maker will not receive hints from the system. The use of consensus methods eliminates this problem, because they enable to solve conflicts of knowledge in near real time. At the same time they guarantee the achievement of a good compromise. However, the effective determination of consensus depends, among other, on the correct definition of the distance function. The aim of this paper is to develop a new distance function between the decisions generated by expert of agents in decision support systems.

引用

页码：155 / 165

页数：11

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