Skip to main content

Auction Equilibrium Strategies for Task Allocation in Uncertain Environments

  • Conference paper
Cooperative Information Agents VIII (CIA 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3191))

Included in the following conference series:

Abstract

In this paper we address a model of self interested information agents competing to perform tasks. The agents are situated in an uncertain environment while different tasks dynamically arrive from a central manager. The agents differ in their capabilities to perform a task under different world states. Previous models concerning cooperative agents aiming for a joint goal are not applicable in such environments, since self interested agents have a motivation to deviate from the joint allocation strategy, in order to increase their own benefits. Given the allocation protocol set by the central manager, a stable solution, is a set of strategies, derived from an equilibrium where no agent can benefit from changing its strategy given the other agents’ strategies. Specifically we focus on a protocol in which, upon arrival of a new task, the central manager starts a reverse auction among the agents, and the agent who bids the lowest cost wins. We introduce the model, formulate its equations and suggest equilibrium strategies for the agents. By identifying specific characteristics of the equilibria, we manage to suggest an efficient algorithm for enhancing the agents’ calculation of the equilibrium strategies. A comparison with the central allocation mechanism, and the effect of environmental settings on the perceived equilibrium are given using several sample environments.

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. Altman, E., Hassin, R.: Non-threshold equilibrium for customers joining an m/g/1 queue. In: Proceedings of 10th International Symposium on Dynamic Game and Applications, Saint-Petersburg, Russia (July 2002)

    Google Scholar 

  2. Boutilier, C., Goldszmidt, M., Sabata, B.: Sequential auctions for the allocation of resources with complementarities. In: IJCAI 1999, pp. 527–523 (1999)

    Google Scholar 

  3. Brandt, F., Brauer, W., Weiss, G.: Task assignment in multiagent systems based on vickrey-type auctioning and leveled commitment contracting. In: Klusch, M., Kerschberg, L. (eds.) CIA 2000. LNCS (LNAI), vol. 1860, pp. 95–106. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  4. Byde, A., Preist, C., Jennings, N.: Decision procedures for multiple auctions. In: AAMAS 2002 (2002)

    Google Scholar 

  5. Dias, B., Stentz, A.: Traderbots: A market-based approach for resource, role, and task allocation in multirobot coordination, Technical Report CMU-RI -TR- 03-19, Robotics Institute, CMU, PA (2003)

    Google Scholar 

  6. McMillan, J., Rothschild, M.: Search. In: Aumann, R.J., Hart, A.S. (eds.) Handbook of Game Theory with Economic Applications, pp. 905–927 (1994)

    Google Scholar 

  7. Sandholm, T., Lesser, V.: Issues in automated negotiation and electronic commerce: Extending the contract net framework. In: ICMAS 1995, pp. 328–335. MIT Press, Cambridge (1995)

    Google Scholar 

  8. Shehory, O.: Optimal bidding in multiple concurrent auctions. International Journal of Cooperative Information Systems 11(3-4), 315–327 (2002)

    Article  Google Scholar 

  9. Smith, R.G.: The contract net protocol: High-level communication and control in a distributed problem solver. IEEE Transactions on Computers 29(12), 1104–1113 (1980)

    Article  Google Scholar 

  10. Smith, T., Sandholm, T., Simmons, R.: Constructing and clearing combinatorial exchanges using preference elicitation, 2002. In: AAAI workshop on Preferences in AI and CP: Symbolic Approaches (2002)

    Google Scholar 

  11. Walsh, W., Wellman, M.: Efficiency and equilibrium in task allocation economies with hierarchical dependencies. In: IJCAI 1999, pp. 520–526 (1999)

    Google Scholar 

  12. Wellman, M., Walsh, W.: Auction protocols for decentralized scheduling. Games and Economic Behavior 35, 271–303 (2001)

    Article  MATH  MathSciNet  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

Sarne, D., Hadad, M., Kraus, S. (2004). Auction Equilibrium Strategies for Task Allocation in Uncertain Environments. In: Klusch, M., Ossowski, S., Kashyap, V., Unland, R. (eds) Cooperative Information Agents VIII. CIA 2004. Lecture Notes in Computer Science(), vol 3191. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30104-2_20

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-30104-2_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23170-7

  • Online ISBN: 978-3-540-30104-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics