On Maximal Classes of Utility Functions for Efficient one-to-one Negotiation
Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence. Pages 941-945.
Abstract
We investigate the properties of an abstract negotiation framework where agents autonomously negotiate over allocations of discrete resources. In this framework, reaching an optimal allocation potentially requires very complex multilateral deals. Therefore, we are interested in identifying classes of utility functions such that any negotiation conducted by means of deals involving only a single resource at at time is bound to converge to an optimal allocation whenever all agents model their preferences using these functions. We show that the class of modular utility functions is not only sufficient but also maximal in this sense.
@inproceedings{ijcai2005p165,
title = {On Maximal Classes of Utility Functions for Efficient one-to-one Negotiation},
author = {Chevaleyre, Yann and Endriss, Ulrich and Maudet, Nicolas},
booktitle = {Proceedings of the Nineteenth International Joint Conference on
Artificial Intelligence, {IJCAI-05}},
publisher = {International Joint Conferences on Artificial Intelligence},
pages = {941--945},
year = {2005},
url = {https://ijcai.org/proceedings/2005/165},
}
TY - CPAPER TI - On Maximal Classes of Utility Functions for Efficient one-to-one Negotiation AU - Chevaleyre, Yann AU - Endriss, Ulrich AU - Maudet, Nicolas T2 - Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, IJCAI-05 PB - International Joint Conferences on Artificial Intelligence PY - 2005 SP - 941 EP - 945 UR - https://ijcai.org/proceedings/2005/165 ER -Copied
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