Skip to main content

Towards a Characterization of Polynomial Preference Elicitation with Value Queries in Combinatorial Auctions

(Extended Abstract)

  • Conference paper
Learning Theory (COLT 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3120))

Included in the following conference series:

Abstract

Communication complexity has recently been recognized as a major obstacle in the implementation of combinatorial auctions. In this paper, we consider a setting in which the auctioneer (elicitor), instead of passively waiting for the bids presented by the bidders, elicits the bidders’ preferences (or valuations) by asking value queries. It is known that in the more general case (no restrictions on the bidders’ preferences) this approach requires the exchange of an exponential amount of information. However, in practical economic scenarios we might expect that bidders’ valuations are somewhat structured. In this paper, we consider several such scenarios, and we show that polynomial elicitation in these cases is often sufficient. We also prove that the family of “easy to elicit” classes of valuations is closed under union. This suggests that efficient preference elicitation is possible in a scenario in which the elicitor, contrary to what it is commonly assumed in the literature on preference elicitation, does not exactly know the class to which the function to elicit belongs. Finally, we discuss what renders a certain class of valuations “easy to elicit with value queries”.

This work is supported in part by NSF under CAREER Award IRI-9703122, Grant IIS-9800994, ITR IIS-0081246, and ITR IIS-0121678.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Angluin, D.: Queries and Concept Learning. Machine Learning 2, 319–342 (1988)

    Google Scholar 

  2. Blum, A., Jackson, J., Sandholm, T., Zinkevic, M.: Preference Elicitation and Query Learning. In: Proc. Conference on Computational Learning Theory, COLT (2003)

    Google Scholar 

  3. Blumrosen, L., Nisan, N.: Auctions with Severely Bounded Communication. In: Proc. IEEE Symposium on Foundations of Computer Science (FOCS), pp. 406–415 (2002)

    Google Scholar 

  4. Bonaccorsi, B., Codenotti, N., Dimitri, M., Leoncini, G., Resta, P.: Generating Realistic Data Sets for Combinatorial Auctions. In: Proc. IEEE Conf. on Electronic Commerce (CEC), pp. 331–338 (2003)

    Google Scholar 

  5. Clarke, E.H.: Multipart Pricing of Public Goods. Public Choice 11, 17–33 (1971)

    Article  Google Scholar 

  6. Conen, W., Sandholm, T.: Preference Elicitation in Combinatorial Auctions. In: Proc. ACM Conference on Electronic Commerce EC, pp. 256–259 (2001); A more detailed description of the algorithmic aspects appeared in the IJCAI-2001 Workshop on Economic Agents, Models, and Mechanisms, pp. 71–80

    Google Scholar 

  7. Conen, W., Sandholm, T.: Partial-Revelation VCG Mechanisms for Combinatorial Auctions. In: Proc. National Conference on Artificial Intelligence (AAAI), pp. 367–372 (2002)

    Google Scholar 

  8. Conitzer, V., Sandholm, T., Santi, P.: On K-wise Dependent Valuations in Combinatorial Auctions. internet draft

    Google Scholar 

  9. de Vries, S., Vohra, R.: Combinatorial Auctions: a Survey. INFORMS J. of Computing (2003)

    Google Scholar 

  10. Goldman, S., Kearns, M.J.: On the Complexity of Teaching. Journal of Computer and System Sciences 50(1), 20–31 (1995)

    Article  MATH  MathSciNet  Google Scholar 

  11. Groves, T.: Incentive in Teams. Econometrica 41, 617–631 (1973)

    Article  MATH  MathSciNet  Google Scholar 

  12. Hudson, B., Sandholm, T.: Effectiveness of Query Types and Policies for Preference Elicitation in Combinatorial Auctions. In: International Joint Conference on Autonomous Agents and Multi Agent Systems, AAMAS 2004 (2004)

    Google Scholar 

  13. Lehmann, D., Ita O’Callaghan, L., Shoham, Y.: Truth Revelation in Approximately Efficient Combinatorial Auctions. Journal of the ACM 49 (5), 577–602 (2002)

    Article  MathSciNet  Google Scholar 

  14. MacKie-Mason, J., Varian, H.R.: Generalized Vickrey Auctions. working paper, Univ. of Michigan (1994)

    Google Scholar 

  15. Nisan, N., Segal, I.: The Communication Requirements of Efficient Allocations and Supporting Lindhal Prices. internet draft (2003)

    Google Scholar 

  16. Rothkopf, M.H., Pekec, A., Harstad, R.H.: Computationally Managable Combinatorial Auctions. Management Science 44(8), 1131–1147 (1998)

    Article  MATH  Google Scholar 

  17. Sandholm, T., Suri, S.: BOB: Improved Winner Determination in Combinatorial Auctions and Generalizations. Artificial Intelligence 145, 33–58 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  18. Sandholm, T.: Algorithm for Optimal Winner Determination in Combinatorial Auctions. Artificial Intelligence 135, 1–54 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  19. Santi, P., Conitzer, V., Sandholm, T.: Towardsa a Characterization of Polynomial Preference Elicitation with Value Queries in Combinatorial Auctions. internet draft, available at http://www.imc.pi.cnr.it/~santi

  20. Vickrey, W.: Counterspeculation, Auctions, and Competitive Sealed Tenders. Journal of Finance 16, 8–37 (1961)

    Article  Google Scholar 

  21. Zinkevich, M., Blum, A., Sandholm, T.: On Polynomial-Time Preference Elicitation with Value Queries. In: Proc. ACM Conference on Electronic Commerce (EC), pp. 176–185 (2003)

    Google Scholar 

  22. Zurel, E., Nisan, N.: An Efficient Approximate Allocation Algorithm for Combinatorial Auctions. In: Proc. 3rd ACM Conference on Electronic Commerce (EC), pp. 125–136 (2001)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Santi, P., Conitzer, V., Sandholm, T. (2004). Towards a Characterization of Polynomial Preference Elicitation with Value Queries in Combinatorial Auctions . In: Shawe-Taylor, J., Singer, Y. (eds) Learning Theory. COLT 2004. Lecture Notes in Computer Science(), vol 3120. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27819-1_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-27819-1_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22282-8

  • Online ISBN: 978-3-540-27819-1

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics