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<article-title>A Pareto Optimal Model for Automated Multi-attribute Negotiations</article-title>
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<author><a href="mailto:guomingl@andrew.cmu.edu"><name>Guoming Lai</name></a></author>
<aff>Tepper School of Business, Carnegie Mellon University, 5000 Forbes Avenue Pittsburgh, PA 15213, USA</aff>

<author><a href="mailto:katia@cs.cmu.edu"><name>Katia Sycara</name></a></author>
<aff>Robotics Institute, Carnegie Mellon University, 5000 Forbes Avenue Pittsburgh, PA 15213, USA</aff>

<author><a href="mailto:Cuihong.Li@business.uconn.edu"><name>Cuihong Li</name></a></author>
<aff>School of Business, University of Connecticut, 2100 Hillside Road Storrs, CT 06269, USA</aff>

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<title>ABSTRACT</title>
<p>This paper presents an applicable model for complex multi-attribute negotiations between autonomous agents. The model adopts a novel protocol which decomposes the original <italic>n</italic>-dimensional negotiation space into a series of negotiation base lines and in each period agents negotiate locally based on a given base line. A belief based negotiation strategy and an offer enhancement process are proposed for agents to make base offer on the negotiation base line and search for Pareto optimal enhancements of the base offer. The model achieves asymptotic Pareto optimality.</p>
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