Arrow Research search
Back to IJCAI

IJCAI 2007

Conference Paper Multiagent Systems Artificial Intelligence

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.

Authors

Keywords

No keywords are indexed for this paper.

Context

Venue
International Joint Conference on Artificial Intelligence
Archive span
1969-2025
Indexed papers
14525
Paper id
1077052703371083329
v2026.09.13