Skip to main content

A multi-agent environment for department of defense distribution

  • Workshop Contributions
  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1042))

Abstract

The United States Department of Defense (DoD) requires an effective, economic method for utilizing the available distribution system to move its personnel, equipment and supplies in support of military operations world wide. Recent reductions in the DoD budget have placed a premium on leveraging technologically innovative solutions to accomplish this requirement. This paper examines the integration of cooperative autonomous computational agent technology with cost effective Low-Earth Orbit (LEO) satellite communications capability. Under this concept, Intelligent Agents (IA) would be developed and integrated into the spectrum of transportation actions DoD wide. The IA would be divided into two categories, static (attached to intermodal sites) and mobile (attached to shipments). The IA act as economic competitors in routing the shipments through the DoD transportation network. The result being effective and efficient transportation of goods and personnel for both routine operations and unforeseen contingencies. The global communication system offered by the LEO satellites would be used to track shipment status and continually update the shared intermodal knowledge base.

This is a preview of subscription content, log in via an institution.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Commerce Business Daily, 24 October 1994.

    Google Scholar 

  2. D. Ferguson, Y. Yemini, and C. Nikalson, “Microeconomic Algorithms for Load Balancing in Distributed Computer Systems,” Research Report, IBM T.J. Watson Research Center, Yorktown Heights, NY, October 1989.

    Google Scholar 

  3. Les Gasser, “Social Conceptions of Knowledge and Action: DAI Foundations and Open Systems,” Artificial Intelligence, Vol. 47, pp. 107–138, 1991.

    Google Scholar 

  4. F. Hahn, “Stability,” in K. Arrow and M. Intriligator, eds., Handbook of Mathematical Economics II, Chapter 16, North Holland Publishing Co., 1982.

    Google Scholar 

  5. Carl Hewitt, “Open Information Systems Semantics for Distributed Artificial Intelligence,” Artificial Intelligence, Vol. 47, pp. 79–106, 1991.

    Google Scholar 

  6. Carl Hewitt and Jeff Inman, “DAI Betwixt and Between: From ‘Intelligent Agents’ to Open Systems Science,” IEEE Transactions on Systems, Man, and Cybernetics, Vol. 21, No. 6, pp. 1409–1419, November/December 1991.

    Google Scholar 

  7. Adrian Hopgood, Knowledge Based Systems, CRC Press, London, England, 1993.

    Google Scholar 

  8. Michael N. Huhns, “Decentralized Logistics Using Autonomous Agent Technology,” (unpublished white paper), Microelectronics and Computer Technology Corporation, Austin, TX, November 1994.

    Google Scholar 

  9. Michael N. Huhns and David M. Bridgeland, “Multiagent Truth Maintenance,” IEEE Transactions on Systems, Man, and Cybernetics, Vol. 21, No. 6, pp. 1437–1445, November/December 1991.

    Google Scholar 

  10. J. O. Kephart, T. Hogg, and B. A. Huberman, “Dynamics of Computational Ecosystems: Implications for DAI,” in Les Gasser and Michael N. Huhns, eds., Distributed Artificial Intelligence, vol. II, Morgan Kaufmann Publishers, Inc., San Mateo, CA, 1989.

    Google Scholar 

  11. L.L. Lee and M.A. Cohen, “Multi-Agent Customer Allocation in a Stochastic Service System,” Management Science, vol. 31, pp. 752–763, June 1985.

    Google Scholar 

  12. Munindar P. Singh and Michael N. Huhns, “Automating Workflows for Service Order Processing: Integrating AI and Database Technologies,” IEEE Expert, October 1994.

    Google Scholar 

  13. United States Transportation Command, “Reengineering the Defense Transportation System: the DTS 2010 Action Plan”, 1994.

    Google Scholar 

  14. Michael P. Wellman, “A General Equilibrium Approach to Distributed Transportation Planning,” Proceedings AAAI-92, San Jose, CA, July 1992, pp. 282–289.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Gerhard Weiß Sandip Sen

Rights and permissions

Reprints and permissions

Copyright information

© 1996 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Glicoes, L., Staats, R., Huhns, M. (1996). A multi-agent environment for department of defense distribution. In: Weiß, G., Sen, S. (eds) Adaption and Learning in Multi-Agent Systems. IJCAI 1995. Lecture Notes in Computer Science, vol 1042. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60923-7_19

Download citation

  • DOI: https://doi.org/10.1007/3-540-60923-7_19

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-60923-0

  • Online ISBN: 978-3-540-49726-4

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics