Combinatorial auctions with k-wise dependent valuations

  • Authors:

  • Vincent Conitzer;Tuomas Sandholm;Paolo Santi

  • Affiliations:

  • Carnegie Mellon University, Computer Science Department, Pittsburgh, PA;Carnegie Mellon University, Computer Science Department, Pittsburgh, PA;Istituto di Informatica e Telematica, Pisa, Italy

  • Venue:
  • AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
  • Year:
  • 2005

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Abstract

We analyze the computational and communication complexity of combinatorial auctions from a new perspective: the degree of interdependency between the items for sale in the bidders' preferences. Denoting by Gk the class of valuations displaying up to k-wise dependencies, we consider the hierarchy G1 ⊂ G2 ⊂ ... ⊂ Gm, where m is the number of items for sale. We show that the minimum non-trivial degree of interdependency (2-wise dependency) is sufficient to render NP-hard the problem of computing the optimal allocation (but we also exhibit a restricted class of such valuations for which computing the optimal allocation is easy). On the other hand, bidders' preferences can be communicated efficiently (i.e., exchanging a polynomial amount of information) as long as the interdependencies between items are limited to sets of cardinality up to k, where k is an arbitrary constant. The amount of communication required to transmit the bidders' preferences becomes super-polynomial (under the assumption that only value queries are allowed) when interdependencies occur between sets of cardinality g(m), where g(m) is an arbitrary function such that g(m) → ∞ as m → ∞. We also consider approximate elicitation, in which the auctioneer learns, asking polynomially many value queries, an approximation of the bidders' actual preferences.