Skip to main content

Multi-auction Approach for Solving Task Allocation Problem

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4078))

Abstract

Request for Proposal (RFP) problem is a type of task allocation problem where task managers need to recruit service provider agents to handle complex tasks composed of multiple sub-tasks, with the objective being to assign each sub-task to a capable agent while keeping the cost as low as possible. Most existing approaches either involve centralized algorithms or require each agent’s cost for doing each sub-task to be known publicly beforehand, or attempt to force the agents to disclose such information by means of truth-telling mechanism, which is not practical in many problems where such information is sensitive and private. In this paper, we present an efficient multi-auction based mechanism that can produce near-optimal solutions without violating the privacy of the participating agents. By including an extra verification step after each bid, we can guarantee convergence to a solution while achieving optimal results in over 97% of the times in a series of experiment.

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   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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Osborne, M.J., Rubinstein, A.: A Course in Game Theory. The MIT Press, Cambridge (1994)

    MATH  Google Scholar 

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

    Article  MathSciNet  Google Scholar 

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

    Article  Google Scholar 

  4. Groves, T.: Incentives in teams. Econometrica 41, 617–631 (1973)

    Article  MathSciNet  MATH  Google Scholar 

  5. Czumaj, A., Ronen, A.: On The Expected Payment of Mechanisms for Task Allocation. In: Proceedings of The Twenty-third Annual ACM Symposium on Principles of Distributed Computing, pp. 252–253 (2004)

    Google Scholar 

  6. Cherkassky, B.V., Goldberg, A.V., Martin, P., Setubal, J.C., Stolfi, J.: Augment or Push? A Computational Study of Bipartite Matching and Unit Capacity Maximum Flow Algorithms. ACM Journal of Experimental Algorithmics 3(8) (1998)

    Google Scholar 

  7. Kraus, S., Shehory, O., Taase, G.: Coalition Formation with Uncertain Heterogeneous Information. In: Proceedings of 2nd International Conference on Autonomous Agents and Multi-Agent Systems, pp. 1–8 (2003)

    Google Scholar 

  8. Kraus, S., Shehory, O., Taase, G.: The Advantages of Compromising in Coalition Formation with Incomplete Information. In: Proceedings of 3rd International Conference on Autonomous Agents and Multi-Agent Systems, pp. 588–595 (2004)

    Google Scholar 

  9. FIPA Iterated Contract Net Interaction Protocol Specification, http://www.fipa.org/specs/fipa00030/

  10. Zhang, H.-J., Li, Q.-H., Ruan, Y.-L.: Resource Co-allocation Via Agent-based Coalition Formation in Computational Grids. In: 2003 International Conference on Machine Learning and Cybernetics, vol. 3, pp. 1936–1940 (2003)

    Google Scholar 

  11. Nisan, N.: Algorithms for Selfish Agents: Mechanism Design for Distributed Computation. In: Meinel, C., Tison, S. (eds.) STACS 1999. LNCS, vol. 1563, pp. 1–17. Springer, Heidelberg (1999)

    Chapter  Google Scholar 

  12. Issac, M., Salmon, T.C., Zillante, A.: A Theory of Jump Bidding in Ascending Auctions, Game Theory and Information 0404002, EconWPA (2004)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Chan, CK., Leung, HF. (2009). Multi-auction Approach for Solving Task Allocation Problem. In: Lukose, D., Shi, Z. (eds) Multi-Agent Systems for Society. PRIMA 2005. Lecture Notes in Computer Science(), vol 4078. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03339-1_20

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-03339-1_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03337-7

  • Online ISBN: 978-3-642-03339-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics