Abstract The interdependencies among attributes make the utility functions of agents much more complex and consequently and the multi-attribute negotiation more difficult. A negotiation model based on generalized additive independence (GAI) multi-attribute dependence is proposed. In this model, GAI decomposition is employed to represent non-linear utility functions of agents as the subutilities of subsets of interdependent attributes. During the procedure of negotiation, each negotiation agent adopts different conceding and proposing strategies to change the offers' content. Seller agent combines the GAI-networks of negotiation participants with the proposed combination algorithm, and produces an offer which maximizes the estimation of social welfare using the GAI tree. Experimental results show that Pareto-optimality agreements can be reached when buyer agent adopts local conceding strategy and seller agent uses global conceding strategy.
2008, Vol. 21 
