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NEGOTIATION IN A MULTI-AGENT SYSTEM FOR CONSTRUCTION CLAIMS NEGOTIATION 

Authors: Z. Ren;  C. J. Anumba; O. O. Ugwu
DOI: 10.1080/08839510290030273
Publication Frequency: 10 issues per year
Published in: journal Applied Artificial Intelligence, Volume 16, Issue 5 May 2002 , pages 359 - 394
Number of References: 55
Formats available: PDF (English)
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Abstract

Negotiation is an important approach for agents to co-operate and reach agreement in multiagent 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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