Computationally Manageable Combinational Auctions
Management Science
Towards a universal test suite for combinatorial auction algorithms
Proceedings of the 2nd ACM conference on Electronic commerce
Algorithm for optimal winner determination in combinatorial auctions
Artificial Intelligence
Taming the Computational Complexity of Combinatorial Auctions: Optimal and Approximate Approaches
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
A Combinatorial Auction with Multiple Winners for Universal Service
Management Science
Distributed Implementations of Vickrey-Clarke-Groves Mechanisms
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
Combinatorial Auctions
Algorithms for distributed winner determination in combinatorial auctions
AMEC'05 Proceedings of the 2005 international conference on Agent-Mediated Electronic Commerce: designing Trading Agents and Mechanisms
Evolutionary dynamics for designing multi-period auctions
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3
Approximate bidding algorithms for a distributed combinatorial auction
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3
Auctions and bidding: A guide for computer scientists
ACM Computing Surveys (CSUR)
On bidding algorithms for a distributed combinatorial auction
Multiagent and Grid Systems
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Distributed allocation and multiagent coordination problems can be solved through combinatorial auctions. However, most of the existing winner determination algorithms for combinatorial auctions are centralized. The PAUSE auction is one of a few efforts to release the auctioneer from having to do all the work (it might even be possible to get rid of the auctioneer). It is an increasing price combinatorial auction that naturally distributes the problem of winner determination amongst the bidders in such a way that they have an incentive to perform the calculation. It can be used when we wish to distribute the computational load among the bidders or when the bidders do not wish to reveal their true valuations unless necessary. PAUSE establishes the rules the bidders must obey. However, it does not tell us how the bidders should calculate their bids. We have developed a couple of bidding algorithms for the bidders in a PAUSE auction. Our algorithms always return the set of bids that maximizes the bidder's utility. Since the problem is NP-Hard, run time remains exponential on the number of items, but it is remarkably better than an exhaustive search. In this paper we present our bidding algorithms, discuss their virtues and drawbacks, and compare the solutions obtained by them to the revenue-maximizing solution found by a centralized winner determination algorithm.