Most of the prior work on multi-attribute negotiations usually assumes that agents have linear additive utility functions on the attributes (e.g. [9, 11, 13]), or focuses on issue-by-issuenegotiations [1, 3]. The work that addresses complex utility functions and Pareto optimality, either assumes complete information, cooperative agents, the presence of a non-biased mediator [7], or makes the assumption that attributes have binary values [6,16,24]. This chapter aims to propose a model that can help agents negotiate multiple attributes with complex utility functions and incomplete information, but still maintains Pareto optimality. Thus, this chapter contributes to the existing literature in the following aspects: first, focusing on decentralized negotiations, our model can be applied to the situations with self-interested agents; second, the model allows agents to negotiate multiple attributes simultaneously and considers Pareto optimality of the negotiation outcome; third, the model can be applied to incomplete information scenarios where each agent knows neither the utility function nor the negotiation strategy of her opponent; and finally, the model can be applied to general situations where agents have complex utility functions in continuous negotiation domains.

The rest of the chapter is organized as follows. Section 2 reviews the related work. Section 3 presents the model. Experimental analysis is provided in Sect. 4, and in Sect. 5 we conclude.