ML Anthology

On Maximal Classes of Utility Functions for Efficient One-to-One Negotiation

Yann Chevaleyre, Ulle Endriss, Nicolas Maudet
IJCAI 2005 pp. 941-946
/ijcai/2005/chevaleyre2005ijcai-maximal/

Abstract

We investigate the properties of an abstract negotiation framework where agents autonomously negotiate over allocations of discrete resources. In
\nthis framework, reaching an optimal allocation potentially requires very complex multilateral deals.
\nTherefore, we are interested in identifying classes
\nof utility functions such that any negotiation conducted by means of deals involving only a single resource at time is bound to converge to an optimal
\nallocation whenever all agents model their preferences using these functions. We show that the class
\nof modular utility functions is not only sufficient
\nbut also maximal in this sense.

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Text

Chevaleyre et al. "On Maximal Classes of Utility Functions for Efficient One-to-One Negotiation." International Joint Conference on Artificial Intelligence, 2005.

Markdown

[Chevaleyre et al. "On Maximal Classes of Utility Functions for Efficient One-to-One Negotiation." International Joint Conference on Artificial Intelligence, 2005.](https://mlanthology.org/ijcai/2005/chevaleyre2005ijcai-maximal/)

BibTeX

@inproceedings{chevaleyre2005ijcai-maximal,
  title     = {{On Maximal Classes of Utility Functions for Efficient One-to-One Negotiation}},
  author    = {Chevaleyre, Yann and Endriss, Ulle and Maudet, Nicolas},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2005},
  pages     = {941-946},
  url       = {https://mlanthology.org/ijcai/2005/chevaleyre2005ijcai-maximal/}
}