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The Effect of Grouping Issues in Multiple Interdependent Issues Negotiation based on Cone-Constraints

  • Katsuhide Fujita
  • Takayuki Ito
  • Mark Klein
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 383)

Abstract

Most real-world negotiation involves multiple interdependent issues, which create agent utility functions that are nonlinear. In this paper, we employ utility functions based on “cone-constraints,” which is more realistic than previous formulations. Cone-constraints capture the intuition that agents’ utilities for a contract usually decline gradually, rather than step-wise, with distance from their ideal contract. In addition, one of the main challenges in developing effective nonlinear negotiation protocols is scalability; they can produce excessively high failure rates, when there are many issues, due to computational intractability. In this paper, we propose the scalable and efficient protocols by grouping Issues. Our protocols can reduce computational cost, while maintaining good quality outcomes, with decomposing the utility space into several largely independent sub-spaces. We also demonstrate that our proposed protocol is highly scalable when compared to previous efforts in a realistic experimental setting.

Keywords

Utility Function Optimality Rate Utility Space Negotiation Protocol Distribution Case 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringNagoya Institute of TechnologyNagoyaJapan
  2. 2.School of Techno-Business AdministrationNagoya Institute of TechnologyNagoyaJapan
  3. 3.Sloan School of ManagementMassachusetts Institute of TechnologyCambridgeU.S.

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