Sequential Bundle-Bid Single-Sale Auction Algorithms for Decentralized Control
Proceedings of the Twentieth International Joint Conference on Artificial Intelligence. Pages 1359-1364.
Abstract
We study auction-like algorithms for the distributed allocation of tasks to cooperating agents. To reduce the team cost of sequential single-item auction algorithms, we generalize them to assign more than one additional task during each round, which increases their similarity to combinatorial auction algorithms. We show that, for a given number of additional tasks to be assigned during each round, every agent needs to submit only a constant number of bids per round and the runtime of winner determination is linear in the number of agents. The communication and winner determination costs do not depend on the number of tasks and thus scale to a large number of tasks for small bundle sizes. We then demonstrate empirically that the team cost of sequential bundle-bid single-sale (= single-item) auction algorithms can be substantially smaller than that without bundles for multi-agent routing problems with capacity constraints.
@inproceedings{ijcai2007p219,
title = {Sequential Bundle-Bid Single-Sale Auction Algorithms for Decentralized Control},
author = {Koenig, Sven and Tovey, Craig A. and Zheng, Xiaoming and Sungur, Ilgaz},
booktitle = {Proceedings of the Twentieth International Joint Conference on
Artificial Intelligence, {IJCAI-07}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Ramon López de Mántaras},
pages = {1359--1364},
year = {2007},
url = {https://ijcai.org/proceedings/2007/219},
}
TY - CPAPER TI - Sequential Bundle-Bid Single-Sale Auction Algorithms for Decentralized Control AU - Koenig, Sven AU - Tovey, Craig A. AU - Zheng, Xiaoming AU - Sungur, Ilgaz T2 - Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, IJCAI-07 PB - International Joint Conferences on Artificial Intelligence PY - 2007 SP - 1359 EP - 1364 UR - https://ijcai.org/proceedings/2007/219 ER -Copied
Machine-readable versions of this paper, for tools and AI agents: