@InProceedings{mendoza07a,
  author =	 {Benito Mendoza and Jos\'{e} M. Vidal},
  title =	 {Bidding Algorithms for a Distributed Combinatorial
                  Auction},
  booktitle =	 {Proceedings of the Autonomous Agents and Multi-Agent
                  Systems Conference},
  year =	 2007,
  abstract =	 {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.},
  comment = 	 {20\% acceptance rate.},
  url = 	 {http://jmvidal.cse.sc.edu/papers/mendoza07a.pdf},
  cluster = 	 {14559246678977872068}
}