Skip to main content
SpringerLink
Log in

Auction design with costly preference elicitation

  • Published:
Annals of Mathematics and Artificial Intelligence Aims and scope Submit manuscript

Abstract

We consider auction design in a setting with costly preference elicitation. Well designed auctions can help to avoid unnecessary elicitation while determining efficient allocations. Careful design can also lead to more efficient outcomes when elicitation is too costly to permit perfect allocative efficiency. An incremental revelation principle is developed and used to motivate the role of proxied and indirect auction designs. Proxy agents, situated between bidders and an auction, can be used to maintain partial information about bidder preferences, to compute equilibrium bidding strategies based on the available information, and to elicit additional preference information as required. We derive information-theoretic elicitation policies for proxy agents under a simple model of costly elicitation across different auction designs. An experimental analysis demonstrates that indirect mechanisms, such as ascending-price auctions, can achieve better allocative efficiency with less preference elicitation than sealed-bid (direct) auctions because they promote better decisions about preference elicitation.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. A. Archer and E. Tardos, Truthful mechanisms for one-parameter agents, in: Proc. 42nd IEEE Symp. on Foundations of Computer Science (2001).

  2. A. Blum, J. Jackson, T. Sandholm and M. Zinkevich, Preference elicitation and query learning, Journal of Machine Learning Research 5 (2004) 649–667.

    Google Scholar 

  3. L. Blumrosen and N. Nisan, Auctions with severely bounded communication, in: Proc. 43rd Annual Symposium on Foundations of Computer Science (2002).

  4. L. Blumrosen, N. Nisan and I. Segal, Multi-player and multi-round auctions with severely bounded communication, in: Proc. 11th Annual European Symposium on Algorithms (2003).

  5. E. Cantillon and M. Pesendorfer, Auctioning bus routes: The London experience, in: Combinatorial Auctions, eds. P. Cramton, Y. Shoham and R. Steinberg (MIT Press, 2006) Chapter 22.

  6. C. Caplice and Y. Sheffi, Combinatorial auctions for truckload transportation, in: Combinatorial Auctions, eds. P. Cramton, Y. Shoham and R. Steinberg (MIT Press, 2006) Chapter 21.

  7. O. Compte and P. Jehiel, On the virtues of the ascending price auction: New insights in the private value setting, Technical report, CERAS and UCL (2000).

  8. O. Compte and P. Jehiel, Auctions and information acquisition: Sealed-bid or dynamic formats?, Technical report, CERAS and UCL (2002).

  9. W. Conen and T. Sandholm, Preference elicitation in combinatorial auctions, in: Proc. 3rd ACM Conf. on Electronic Commerce (EC-01) (2001) pp. 256–259.

  10. V. Conitzer and T. Sandholm, Computational criticisms of the revelation principle, in: Proc. AAMAS Workshop on Agent Mediated Electronic Commerce (AMEC V), Melbourne, Australia (2003).

  11. S. de Vries, J. Schummer and R. V. Vohra, On ascending Vickrey auctions for heterogeneous objects, Technical report MEDS, Kellogg School, Northwestern University (2004).

  12. C. Ehrman and M. Peters, Sequential selling mechanisms, Economic Theory 4 (1994) 237–253.

    Article  Google Scholar 

  13. K. Fong, Multi-stage information acquisition in auction design, Master’s thesis, Harvard University (2003).

  14. A. Gibbard, Manipulation of voting schemes: A general result, Econometrica 41 (1973) 587–602.

    Google Scholar 

  15. J. Green and J.-J. Laffont, Characterization of satisfactory mechanisms for the revelation of preferences for public goods, Econometrica 45 (1977) 427–438.

    Google Scholar 

  16. A. Greenwald and J.O. Kephart, Shopbots and pricebots, in: Proc. 16th International Joint Conference on Artificial Intelligence (IJCAI-99) (1999) pp. 506–511.

  17. R. Holzman, N. Kfir-Dahav, D. Monderer and M. Tennenholtz, Bundling equilibrium in combinatorial auctions, Games and Economic Behavior 47(1) (2004) 104–123.

    Article  Google Scholar 

  18. B. Hudson and T. Sandholm, Effectiveness of query types and policies for preference elicitation in combinatorial auctions, in: Proc. 3rd Int. Joint. Conf. on Autonomous Agents and Multi Agent Systems (2004) pp. 386–393.

  19. M.O. Jackson, Mechanism theory, in: The Encyclopedia of Life Support Systems (EOLSS Publishers, 2000).

  20. C.D. Kolstad and R.M. Guzman, Information and the divergence between willingness-to-accept and willingness-to-pay, J. Env. Econ. Manag. 38(1) (1999) 66–80.

    Article  Google Scholar 

  21. S.M. Lahaie and D.C. Parkes, Applying learning algorithms to preference elicitation, in: Proc. ACM Conf. on Electronic Commerce (2004) pp. 180–188.

  22. K. Larson and T. Sandholm, Bargaining with limited computation: Deliberation equilibrium, Artificial Intelligence 132(2) (2001) 183–217.

    Article  Google Scholar 

  23. K. Larson and T. Sandholm, Experiments on deliberation equilibria in auctions, in: Proc. 3rd Int. Joint. Conf. on Autonomous Agents and Multi Agent Systems (2004) pp. 394–401.

  24. K. Larson and T.W. Sandholm, Costly valuation computation in auctions, in: Proc. Theoretical Aspects of Rationality and Knowledge VII (2001) pp. 169–182.

  25. J.O. Ledyard, The design of coordination mechanisms and organizational computing, Journal of Organizational Computing 1 (1993) 121–134.

    Google Scholar 

  26. T.K. Lee, Competition and information acquisition in first price auctions, Economic Letters 19 (1985) 129–132.

    Article  Google Scholar 

  27. D. Lehmann, R. Muller and T. Sandholm, The winner determination problem, in: Combinatorial Auctions, eds. P. Cramton, Y. Shoham and R. Steinberg (MIT Press, 2004) Chapter 12.

  28. D. Lehmann, L.I. O’Callaghan and Y. Shoham, Truth revelation in approximately efficient combinatorial auctions, Journal of the ACM 49(5) (2002) 577–602.

    Article  Google Scholar 

  29. D. Levin and J.L. Smith, Equilibrium in auctions with entry, American Economic Review 64 (1994) 585–599.

    Google Scholar 

  30. A. Mas-Colell, M.D. Whinston and J.R. Green, Microeconomic Theory (Oxford University Press, Oxford, 1995).

    Google Scholar 

  31. R.P. McAfee and J. McMillan, Analyzing the airwaves auction, J. Econ. Perspect. 10 (1996) 159–175.

    PubMed  Google Scholar 

  32. P. Milgrom and R. Weber, A theory of auctions and competitive bidding, Econometrica 50 (1982) 1089–1122.

    Google Scholar 

  33. D. Mishra and D. Parkes, Ascending price Vickrey auctions for general valuations, Technical report, Harvard University (2005).

  34. N. Nisan, Bidding languages for combinatorial auctions, in: Combinatorial Auctions, eds. P. Cramton, Y. Shoham and R. Steinberg (MIT Press, 2006) Chapter 9.

  35. N. Nisan and I. Segal, The communication requirements of efficient allocations and supporting prices, Journal of Economic Theory (2005) to appear.

  36. D.C. Parkes, Iterative combinatorial auctions: Achieving economic and computational efficiency, Ph.D. thesis, Department of Computer and Information Science, University of Pennsylvania (2001).

  37. D.C. Parkes, Price-based information certificates for minimal-revelation combinatorial auctions, in: Agent Mediated Electronic Commerce IV: Designing Mechanisms and Systems, Lecture Notes in Artificial Intelligence, Vol. 2531 (2002) pp. 103–122.

  38. D.C. Parkes and J. Kalagnanam, Models for iterative multiattribute procurement auctions, Management Science 51(3), Special Issue on Electronic Markets (2005) 435–451.

    Google Scholar 

  39. D.C. Parkes and L.H. Ungar, Iterative combinatorial auctions: Theory and practice, in: Proc. 17th National Conference on Artificial Intelligence (AAAI-00) (2000) pp. 74–81.

  40. D.C. Parkes and L.H. Ungar, Preventing strategic manipulation in iterative auctions: Proxy agents and price-adjustment, in: Proc. 17th National Conference on Artificial Intelligence (AAAI-00) (2000) pp. 82–89.

  41. D.M. Reeves and M.P. Wellman, Computing equilibrium strategies in infinite games of incomplete information, in: Proc. of Game-Theoretic and Decision-Theoretic Workshop at AAMAS’03 (2003).

  42. L. Rezende, Mid-auction information acquisition, Technical report, Department of Economics, Stanford University (2001).

  43. A. Ronen, Mechanism design with incomplete languages, in: Proc. 3rd ACM Conf. on Electronic Commerce (EC’01) (2001).

  44. S. Russell and E. Wefald, Principles of metareasoning, Artificial Intelligence 49 (1991) 361–395.

    Article  MathSciNet  Google Scholar 

  45. W.F. Samuelson, Competitive bidding with entry costs, Economic Letters 17 (1985) 53–57.

    Article  Google Scholar 

  46. T.W. Sandholm, An implementation of the Contract Net Protocol based on marginal-cost calculations, in: Proc. 11th National Conference on Artificial Intelligence (AAAI-93) (1993) pp. 256–262.

  47. T.W. Sandholm, Limitations of the Vickrey auction in computational multiagent systems, in: Second International Conference on Multiagent Systems (ICMAS-96) (1996) pp. 299–306.

  48. T.W. Sandholm, Automated negotiation, Communications of the ACM 42(3) (1999) 84–85.

    Article  Google Scholar 

  49. M. Stegeman, Participation costs and efficient auctions, Journal of Economic Theory 71 (1996) 228–259.

    Article  Google Scholar 

  50. A.V. Sunderam and D.C. Parkes, Preference elicitation in proxied multiattribute auctions, in: Fourth ACM Conf. on Electronic Commerce (EC’03) (2003) pp. 214–215.

  51. W. Vickrey, Counterspeculation, auctions, and competitive sealed tenders, Journal of Finance 16 (1961) 8–37.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Division of Engineering and Applied Sciences, Harvard University, 33 Oxford Street, Cambridge, MA, 02138, USA

    David C. Parkes

Authors
  1. David C. Parkes
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to David C. Parkes.

Additional information

A preliminary version of this paper appeared in the Proc. of the IJCAI’99 Workshop on Agent Mediated Electronic Commerce.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Parkes, D.C. Auction design with costly preference elicitation. Ann Math Artif Intell 44, 269–302 (2005). https://doi.org/10.1007/s10472-005-4692-y

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10472-005-4692-y

Keywords

Search

Navigation