Generalizing Envy-Freeness toward Group of Agents
Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 386-391.
Abstract
Envy-freeness is a well-known fairness concept for analyzing mechanisms. Its traditional definition requires that no individual envies another individual. However, an individual (or a group of agents) may envy another group, even if she (or they) does not envy another individual. In mechanisms with monetary transfer, such as combinatorial auctions, considering such fairness requirements, which are refinements of traditional envy-freeness, is meaningful and brings up a new interesting research direction in mechanism design. In this paper, we introduce two new concepts of fairness called envy-freeness of an individual toward a group, and envy-freeness of a group toward a group. They are natural extensions of traditional envy-freeness. We discuss combinatorial auction mechanisms that satisfy these concepts. First, we characterize such mechanisms by focusing on their allocation rules. Then we clarify the connections between these concepts and three other properties: the core, strategy-proofness, and false-name-proofness.
@inproceedings{ijcai2011p73,
title = {Generalizing Envy-Freeness toward Group of Agents},
author = {Todo, Taiki and Li, Runcong and Hu, Xuemei and Mouri, Takayuki and Iwasaki, Atsushi and Yokoo, Makoto},
booktitle = {Proceedings of the Twenty-Second International Joint Conference on
Artificial Intelligence, {IJCAI-11}},
publisher = {AAAI Press/International Joint Conferences on Artificial Intelligence},
editor = {Toby Walsh},
pages = {386--391},
year = {2011},
month = {7},
doi = {10.5591/978-1-57735-516-8/IJCAI11-073},
url = {https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-073},
}
TY - CPAPER TI - Generalizing Envy-Freeness toward Group of Agents AU - Todo, Taiki AU - Li, Runcong AU - Hu, Xuemei AU - Mouri, Takayuki AU - Iwasaki, Atsushi AU - Yokoo, Makoto T2 - Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11 PB - AAAI Press/International Joint Conferences on Artificial Intelligence PY - 2011 SP - 386 EP - 391 DO - 10.5591/978-1-57735-516-8/IJCAI11-073 UR - https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-073 ER -Copied
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