Skip to main content

Abstract

The TAC SCM Prediction Challenge presents an opportunity for agents designed for the full TAC SCM game to compete solely on their ability to make predictions. Participants are presented with situations from actual TAC SCM games and are evaluated on their prediction accuracy in four categories: current and future computer prices, and current and future component prices. This paper introduces the Prediction Challenge and presents the results from 2007 along with an analysis of how the predictions of the participants compare to each other.

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. Collins, J., Arunachalam, R., Sadeh, N., Eriksson, J., Finne, N., Janson, S.: The Supply Chain Management game for the 2007 Trading Agent Competition. Technical report (2006), https://www.sics.se/tac/tac07scmspec.pdf

  2. Pardoe, D., Stone, P.: An autonomous agent for supply chain management. In: Adomavicius, G., Gupta, A. (eds.) Handbooks in Information Systems Series: Business Computing. Elsevier, Amsterdam (2008)

    Google Scholar 

  3. Kiekintveld, C., Miller, J., Jordan, P.R., Callender, L.F., Wellman, M.P.: Forecasting market prices in a supply chain game. Submitted to Electronic Commerce Research Applications (2008)

    Google Scholar 

  4. Witten, I.H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations. Morgan Kaufmann, San Francisco (1999)

    Google Scholar 

  5. Kiekintveld, C., Wellman, M., Singh, S., Estelle, J., Vorobeychik, Y., Soni, V., Rudary, M.: Distributed feedback control for decision making on supply chains. In: Fourteenth International Conference on Automated Planning and Scheduling (2004)

    Google Scholar 

  6. Benisch, M., Sardinha, A., Andrews, J., Sadeh, N.: Cmieux: Adaptive strategies for competitive supply chain trading. In: Eighth International Conference on Electronic Commerce (2006)

    Google Scholar 

  7. Burke, D.A., Brown, K.N., Hnich, B., Tarim, A.: Learning market prices for a real-time supply chain management trading agent. In: AAMAS 2006 Workshop on Trading Agent Design and Analysis/Agent Mediated Electronic Commerce (2006)

    Google Scholar 

  8. Benisch, M., Greenwald, A., Grypari, I., Lederman, R., Naroditskiy, V., Tschantz, M.: Botticelli: A supply chain management agent. In: Third International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), vol. 3, pp. 1174–1181 (2004)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Pardoe, D., Stone, P. (2010). The 2007 TAC SCM Prediction Challenge. In: Ketter, W., La Poutré, H., Sadeh, N., Shehory, O., Walsh, W. (eds) Agent-Mediated Electronic Commerce and Trading Agent Design and Analysis. AMEC TADA 2008 2008. Lecture Notes in Business Information Processing, vol 44. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15237-5_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-15237-5_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15236-8

  • Online ISBN: 978-3-642-15237-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics