Negotiation in a multi-agent system for construction claims negotiation

被引：29
|
作者：
Ren, Z [1 ]
Anumba, CJ [1 ]
Ugwu, OO [1 ]
机构：
[1] Univ Loughborough, Dept Civil & Bldg Environm, Ctr Innovat Construct Engn, Loughborough LE11 3TU, Leics, England
来源：
APPLIED ARTIFICIAL INTELLIGENCE | 2002年 / 16卷 / 05期
关键词：
D O I：
10.1080/08839510290030273
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Negotiation is an important approach for agents to co-operate and reach agreement in multi-agent systems (MAS). Different negotiation theories and models have been deployed in a variety of applications. This paper is concerned with the applicability of these theories to the domain of agent-based construction claims negotiation. The peculiarities of this domain are highlighted and the approach adopted in the development of a multi-agent system for construction claims negotiation (MASCOT) described. Of particular interest is the integration of Zeuthen's bargaining model with a Bayesian learning mechanism, which addresses the characeristics of the construction claims negotiation. Examples are presented to demonstrate the impact of various negotiation approaches on the conduct and outcome of construction claims negotiations.
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页码：359 / 394
页数：36
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