Skip to main content

A Vickrey-Type Multi-attribute Auction Model

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3930))

Abstract

Internet auction is not only an integral part of Electronic Commerce but is also becoming a promising field for applying autonomous agents and multi-agent system (MAS) technologies. And auction, as an efficient resource allocation method, has an important role in MAS problems and as such is receiving increasing attention from scholars. This paper suggests a protocol (VAMA) and strategies for multi-attribute auction. Some useful properties such as strategy-proof are also proven. This paper also includes an analysis of the strategy of the buyer, and gives a decentralized mechanism for VAMA implementation as well as discussing some questions about VAMA. Finally, this protocol is compared with existing ones, improving on the work of Esther David etc.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Takayuki, Suyama, Yokoo, M.: Strategy/ False-name Proof Protocols for Combinatorial Multi-Attribute Procurement Auction. In: AAMAS 2004, New York, USA, July 19-23 (2004)

    Google Scholar 

  2. Yokoo, M.: Characterization of Strategy/False-name Proof Combinatorial Auction Protocols: Price-oriented, Rationing-free Protocol. In: Proceedings of 19th International Joint Conference On Artificial Intelligence (IJCAI 2003), pp. 733–739 (2003)

    Google Scholar 

  3. Sandholm, T., Larson, K., Andersson, M., Shehory, O., Tohme, F.: Coalition structure generation with worst case guarantees. Artificial Intelligence Journal (1999)

    Google Scholar 

  4. Wellman, M., Walsh, W., Wurman, P., MacKie-Mason, J.: Auction protocols for decentralized scheduling. Games and Economic Behavior 35, 271–303 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  5. Hunsberger, L., Grosz, B.J.: A combinatorial auction for collaborative lanning. In: Proc. 4th International Conference on Multi-Agent Systems (ICMAS 2000), pp. 151–158 (2000)

    Google Scholar 

  6. Parkes, D.C., Kalagnanam, J.: Multiattribute Reverse Auctions. Presented at AAAI (2002)

    Google Scholar 

  7. David, E., Azoulay-Schwartz, R., Kraus, S.: An English Auction Protocol for Multi-Attribute Items. In: AMEC 2002, pp. 52–68 (2002)

    Google Scholar 

  8. David, E., Azoulay-Schwartz, R., Kraus, S.: Bidders’ Strategy for Automated Multi-Attribute sequential English Auction with a Deadline. In: The Second International Joint Conference on Autonomous Agents and Multiagent systems, pp. 457–464 (2003)

    Google Scholar 

  9. Bichler, M.: An Experimental Analysis of Multi-Attribute Auctions. Decision Support System 28 (2000)

    Google Scholar 

  10. Bichler, M., BidTaker: An Application of Multi-Attribute Auction Markets in Tourism. Presented and Wirtschaftsinformatik 2002, Augsburg, Germany (2002)

    Google Scholar 

  11. Sandholm, T.: Issues in Computational Vickrey Auctions. International Journal of Electronic Commerce 4(3), 107–129 (2000)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Chen, X., Hu, Sl. (2006). A Vickrey-Type Multi-attribute Auction Model. In: Yeung, D.S., Liu, ZQ., Wang, XZ., Yan, H. (eds) Advances in Machine Learning and Cybernetics. Lecture Notes in Computer Science(), vol 3930. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11739685_3

Download citation

  • DOI: https://doi.org/10.1007/11739685_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-33584-9

  • Online ISBN: 978-3-540-33585-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics