Advertisement

Coordinating Decisions in a Supply-Chain Trading Agent

  • Wolfgang Ketter
  • John Collins
  • Maria Gini
Conference paper
  • 335 Downloads
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 44)

Abstract

An autonomous trading agent is a complex piece of software that must operate in a competitive economic environment. We identify the problem of decision coordination as a crucial element in the design of an agent for TAC SCM, and we review the published literature on agent design to discover a wide variety of approaches to this problem. We believe that the existence of such variety is an indication that much is yet to be learned about designing such agents.

Keywords

Supply Chain Management Production Schedule Reserve Price Customer Demand Supply Market 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Collins, J., Arunachalam, R., Sadeh, N., Ericsson, J., Finne, N., Janson, S.: The Supply Chain Management Game for the 2006 Trading Agent Competition. Technical Report CMU-ISRI-05-132, Carnegie Mellon University, Pittsburgh, PA (2005)Google Scholar
  2. 2.
    Ketter, W., Kryzhnyaya, E., Damer, S., McMillen, C., Agovic, A., Collins, J., Gini, M.: Analysis and design of supply-driven strategies in TAC-SCM. In: Workshop: Trading Agent Design and Analysis at the Third Int’l. Conf. on Autonomous Agents and Multi-Agent Systems, New York, pp. 44–51 (2004)Google Scholar
  3. 3.
    Wellman, M.P., Estelle, J., Singh, S., Vorobeychik, Y., Kiekintveld, C., Soni, V.: Strategic interactions in a supply chain game. Computational Intelligence 21(1), 1–26 (2005)CrossRefMathSciNetGoogle Scholar
  4. 4.
    Kiekintveld, C., Miller, J., Jordan, P.R., Wellman, M.P.: Controlling a Supply Chain Agent Using Value-Based Decomposition. In: Proc. of 7th ACM Conf. on Electronic Commerce, Ann Arbor, USA, pp. 208–217 (2006)Google Scholar
  5. 5.
    Collins, J., Ketter, W., Gini, M.: Flexible decision control in an autonomous trading agent. Electronic Commerce Research and Applications 8(2), 91–105 (2009)CrossRefGoogle Scholar
  6. 6.
    Jordan, P.R., Kiekintveld, C., Wellman, M.P.: Empirical game-theoretic analysis of the tac supply chain game. In: Proc. of the Sixth Int’l. Conf. on Autonomous Agents and Multi-Agent Systems, pp. 1188–1195 (2007)Google Scholar
  7. 7.
    Benisch, M., Greenwald, A., Grypari, I., Lederman, R., Naroditskiy, V., Tschantz, M.: Botticelli: A supply chain management agent designed to optimize under uncertainty. ACM Trans. on Comp. Logic 4(3), 29–37 (2004)Google Scholar
  8. 8.
    He, M., Rogers, A., Luo, X., Jennings, N.R.: Designing a successful trading agent for supply chain management. In: Proc. of the Fifth Int’l. Conf. on Autonomous Agents and Multi-Agent Systems, pp. 1159–1166 (2006)Google Scholar
  9. 9.
    Collins, J., Ketter, W., Gini, M.: Flexible decision support in a dynamic business network. In: Verwest, P., van Liere, D., Zheng, L. (eds.) The Network Experience – New Value from Smart Business Networks, pp. 233–246. Springer, Heidelberg (2008)Google Scholar
  10. 10.
    Collins, J., Ketter, W., Gini, M., Agovic, A.: Software architecture of the MinneTAC supply-chain trading agent. Technical Report 08-031, University of Minnesota, Department of Computer Science and Engineering, Minneapolis, MN (2008)Google Scholar
  11. 11.
    Chatzidimitriou, K.C., Symeonidis, A.L., Kontogounis, I., Mitkas, P.A.: Agent Mertacor: A robust design for dealing with uncertainty and variation in SCM environments. Expert Systems with Applications 35(3), 591–603 (2008)CrossRefGoogle Scholar
  12. 12.
    Kontogounis, I., Chatzidimitriou, K., Symeonidis, A., Mitkas, P.: A Robust Agent Design for Dynamic SCM Environments. In: Antoniou, G., Potamias, G., Spyropoulos, C., Plexousakis, D. (eds.) SETN 2006. LNCS (LNAI), vol. 3955, pp. 127–136. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  13. 13.
    Stan, M., Stan, B., Florea, A.M.: A Dynamic Strategy Agent for Supply Chain Management. In: Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, pp. 227–232 (2006)Google Scholar
  14. 14.
    Podobnik, V., Petric, A., Jezic, G.: The crocodileagent: Research for efficient agent-based cross-enterprise processes. In: Meersman, R., Tari, Z., Herrero, P. (eds.) OTM 2006 Workshops. LNCS, vol. 4277, pp. 752–762. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  15. 15.
    Petric, A., Podobnik, V., Jezic, G.: The CrocodileAgent: Designing a robust trading agent for volatile e-market conditions. In: Nguyen, N.T., Grzech, A., Howlett, R.J., Jain, L.C. (eds.) KES-AMSTA 2007. LNCS (LNAI), vol. 4496, pp. 597–606. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  16. 16.
    Benisch, M., Sardinha, A., Andrews, J., Sadeh, N.: CMieux: adaptive strategies for competitive supply chain trading. In: Proc. of 8th Int’l. Conf. on Electronic Commerce, pp. 47–58. ACM Press, New York (2006)Google Scholar
  17. 17.
    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 (2007)Google Scholar
  18. 18.
    Keller, P.W., Duguay, F.O., Precup, D.: Redagent - winner of the TAC SCM 2003. SIGecom Exchanges 4(3), 1–8 (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Wolfgang Ketter
    • 1
  • John Collins
    • 1
    • 2
  • Maria Gini
    • 1
    • 2
  1. 1.Dept of DISRSM Erasmus UniversityRotterdam
  2. 2.Dept of CSEUniversity of MinnesotaMinneapolisUSA

Personalised recommendations