Skip to main content

How to Make Specialists NOT Specialised in TAC Market Design Competition? Behaviour-Based Mechanism Design

  • Conference paper
Book cover E-Commerce and Web Technologies (EC-Web 2011)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 85))

Included in the following conference series:

  • 923 Accesses

Abstract

This paper proposes an approach to design behaviour-based double auction mechanisms that are adaptive to market changes under the Trading Agent Competition Market Design platform. Because of the dynamics of the market environment, it is not feasible to test a mechanism in all kinds of environments. Since the strategies adopted by traders are well classified and studied, we will analyse and utilise the behaviour of traders with each kind of strategy, design specific (trader-dependent) mechanisms for attracting them, and finally integrate these trader-dependent mechanisms to achieve adaptive mechanisms.

This research was supported by the Australian Research Council through Discovery Project DP0988750.

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 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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. Cai, K., Gerding, E., Mcburney, P., Niu, J., Parsons, S., Phelps, S.: Overview of cat: A market design competition version 2.0. Technical report, University of Liverpool (2009)

    Google Scholar 

  2. Parkes, D.C.: Online mechanisms. In: Algorithmic Game Theory. Cambridge University Press, Cambridge (2007)

    Google Scholar 

  3. Vytelingum, P., Vetsikas, I.A., Shi, B., Jennings, N.R.: Iamwildcat: The winning strategy for the tac market design competition. In: Proceeding of the 18th European Conference on Artificial Intelligence, pp. 428–432 (2008)

    Google Scholar 

  4. Stavrogiannis, L.C., Mitkas, P.A.: Cat 2008 post-tournament evaluation: The mertacors perspective. In: IJCAI Workshop on Trading Agent Design and Analysis (2009)

    Google Scholar 

  5. Honari, S., Ebadi, M., Foshati, A., Gomrokchi, M., Benatahr, J., Khosravifar, B.: Price estimation of persiancat market equilibrium. In: IJCAI Workshop on Trading Agent Design and Analysis, TADA (2009)

    Google Scholar 

  6. Niu, J., Cai, K., Parsons, S.: A grey-box approach to automated mechanism design. In: Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1. AAMAS 2010, pp. 1473–1474 (2010)

    Google Scholar 

  7. Robinson, E., McBurney, P., Yao, X.: How specialised are specialists? Generalisation properties of entries from the 2008 and 2009 TAC market design competitions. In: David, E., Gerding, E., Sarne, D., Shehory, O. (eds.) AMEC 2009. LNBIP, vol. 59, pp. 178–194. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  8. Niu, J., Cai, K., Parsons, S., Gerding, E., McBurney, P., Moyaux, T., Phelps, S., Shield, D.: Jcat: a platform for the tac market design competition. In: AAMAS 2008 (2008)

    Google Scholar 

  9. Gode, D.K., Sunder, S.: Allocative efficiency of markets with zero-intelligence traders: Market as a partial substitute for individual rationality. Journal of Political Economy 101(1), 119–137 (1993)

    Article  Google Scholar 

  10. Cliff, D.: Minimal-intelligence agents for bargaining behaviors in market-based environments. Technical report (1997)

    Google Scholar 

  11. Gjerstad, S., Dickhaut, J.: Price formation in double auctions. In: E-Commerce Agents, Marketplace Solutions, Security Issues, and Supply and Demand, pp. 106–134. Springer, London (2001)

    Google Scholar 

  12. Erev, I., Roth, A.E.: Predicting how people play games: Reinforcement learning in experimental games with unique, mixed strategy equilibria. American Economic Review 88(4), 848–881 (1998)

    Google Scholar 

  13. Friedman, D., Rust, J.: The Double Auction Market: Institutions, Theories, And Evidence. Westview Press, Boulder (1993)

    Google Scholar 

  14. Phelps, S., Mcburney, P., Parsons, S.: Evolutionary mechanism design: a review. Autonomous Agents and Multi-Agent Systems 21, 237–264 (2010)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Zhao, D., Zhang, D., Perrussel, L. (2011). How to Make Specialists NOT Specialised in TAC Market Design Competition? Behaviour-Based Mechanism Design. In: Huemer, C., Setzer, T. (eds) E-Commerce and Web Technologies. EC-Web 2011. Lecture Notes in Business Information Processing, vol 85. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23014-1_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-23014-1_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23013-4

  • Online ISBN: 978-3-642-23014-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics