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Issue title: Negotiation and Scheduling Mechanisms for Multiagent Systems
Guest editors: Kwang Mong Simx, Minjie Zhangy and Takayuki Itoz
Article type: Research Article
Authors: Lai, Guominga; * | Sycara, Katiab | Li, Cuihongc
Affiliations: [a] Tepper School of Business, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA | [b] Robotics Institute, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA | [c] School of Business, University of Connecticut, 2100 Hillside Road, Storrs, CT 06269, USA | [x] Hong Kong Baptist University, Kowloon, Hong Kong, China | [y] University of Wollongong, Wollongong, NSW 2522, Australia | [z] Nagoya Institute of Technology, Gokiso, Showa, Nagoya 466-8555, Japan
Correspondence: [*] Corresponding author. Tel.: +1 412 268 4627; Fax: +1 412 268 5569; E-mail: [email protected]
Abstract: This paper presents a decentralized model that allows self-interested agents to reach “win-win” agreements in a multi-attribute negotiation. The model is based on an alternating-offer protocol. In each period, the proposing agent is allowed to make a limited number of offers. The responding agent can select the best out of these offers. In the case of rejection, agents exchange their roles and the negotiation proceeds to the next period. To make counteroffers, an agent first uses the heuristic of choosing the offer on an indifference (or “iso-utility”) curve/surface that is closest to the best offer made by the opponent in the previous period, and then taking this offer as the seed, chooses several other offers randomly in a specified neighborhood of this seed offer. Experimental analysis shows agents can reach near Pareto optimal agreements in quite general situations following the model where agents may have complex preferences on the attributes and incomplete information. This model does not require the presence of a mediator.
Keywords: Multi-attribute negotiation, pareto optimality, win-win, rational preference, incomplete information, self-interested agents
DOI: 10.3233/MGS-2008-4104
Journal: Multiagent and Grid Systems, vol. 4, no. 1, pp. 45-65, 2008
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