Effective bidding and deal identification for negotiations in highly nonlinear scenarios

  • Authors:

  • Ivan Marsa-Maestre;Miguel A. Lopez-Carmona;Juan R. Velasco;Enrique de la Hoz

  • Affiliations:

  • Universidad de Alcala, Alcala de Henares (Madrid), Spain;Universidad de Alcala, Alcala de Henares (Madrid), Spain;Universidad de Alcala, Alcala de Henares (Madrid), Spain;Universidad de Alcala, Alcala de Henares (Madrid), Spain

  • Venue:
  • Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
  • Year:
  • 2009

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Abstract

Most real-world negotiation scenarios involve multiple, inter-dependent issues. These scenarios are specially challenging because the agents' utility functions are nonlinear, which makes traditional negotiation mechanisms not applicable. Even mechanisms designed and proven useful for nonlinear utility spaces may fail if the utility space is highly nonlinear. For example, simulated annealing has been used successfully in bidding based negotiations with constraint-based utility spaces to identify high utility regions in the contract space, and to send these regions as bids to a mediator. In this paper, we will show that the performance of this approach decreases drastically in highly nonlinear scenarios, and propose alternative mechanisms for the bidding process which take advantage of the constraint-based preference model. Also, we propose a probabilistic search method for the mediator to improve the scalability of the deal identification process, and an iterative, expressive negotiation protocol to give feed-back to the agents in case no deals have been found with the initial bids. The experiments show that the proposed mechanisms yield better results than the previous approach in highly nonlinear negotiation scenarios.