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Multi-agent negotiation algorithms for resources cost estimation: A case study

  • Multi-Agent Systems and Distributed Artificial Intelligence
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Progress in Artificial Intelligence (EPIA 1997)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1323))

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Abstract

In this paper we describe appropriate negotiation protocols we have developed for a multi-agent system whose aim is to advice on distributed resources selection, as well as cost estimation, in big civil construction companies. Prices of each specific resource have an influence on the results of the negotiation algorithm which leads to the best agents (resources) coalition for a given task. Moreover, several interesting problems have been addressed in order to make agents negotiation strategies more competitive and adequate. This is the case of the “self depreciation problem” which arises when an agent (a resource) belongs to more than one coalition which alters its own behaviour during the competition between those coalitions. Our negotiation protocol and agents strategies are able to provide the company with a precise idea about the respective importance of each resource and reach a solution, i.e. find the best set of resources, to deal competitively with the task in hands. Another important factor our approach takes into account during agents negotiation, is the influence of time (date of task announcement, starting and ending task dates) which may guide each agent negotiation strategy according with a forecast of their own employment possibilities in the future. We conclude the paper with a description of a realistic example in the civil construction domain, which illustrates the concepts we have developed.

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References

  1. Coulson-Thomas, C. (1992). Transforming the company. Kogan Page Limited. London.

    Google Scholar 

  2. R. Davis and R. G. Smith, “Negotiation as a Metaphor for Distributed Problem Solving,” Artificial Intelligence, vol. 20, pp. 63–109, 1983.

    Google Scholar 

  3. Fonseca J. M., Oliveira E., Steiger-Garção A. (1996). MACIV-A DAI Based Resource Management System. Proceedings of PAAM'96, pages 263–277, London, UK, April 1996. Also to be published on the International Journal of Applied AI.

    Google Scholar 

  4. Genesereth, M., Ketchpel, S. (1994). Software Agents. Communications of the ACM, Vol. 37, No 7, July 1994, pp. 48–53.

    Google Scholar 

  5. Kambil, A. (1997). Doing Business in the Wired World. IEEE Computer. May 1997, pp. 56–61.

    Google Scholar 

  6. Ketchpel, S. 1993. Coalition Formation Among Autonomous Agents. Lecture Notes in Artificial Intelligence 957, pp. 73–88. Springer Verlag.

    Google Scholar 

  7. Oliveira, E., Garrido, P. (1995). Cognitive Cooperation Facilitators. Proceedings of IEEE Int. Conf. On System, Man and Cybernetics, Vancouver, Canada.

    Google Scholar 

  8. Oliveira, E., Fonseca, J. M., Steiger-Garrção, A. (1996). Agent coalitions, negotiation and strategy adaptation. Proceedings of the 1st Iberoamerican Workshop on Distributed Artificial Intelligence and Multiagent Systems. Pp. 99–108. Xalapa, Mexico.

    Google Scholar 

  9. Pindyck, R., Rubinfeld, D. (1995). Microeconomics. Prentice Hall International. New Jersey.

    Google Scholar 

  10. Rosenschein J. R., Zlotkin G. (1994). Rules of Encounter. MIT Press.

    Google Scholar 

  11. T. W. Sandholm and V. R. Lesser, “Coalition Formation among Bounded Rational Agents” Conference on Artificial Intelligence (IJCAI-95), Montreal, Canada, pp. 662–669.

    Google Scholar 

  12. T. W. Sandholm (1996). “Negotiation among self-interested computationally limited agents”. PhD Dissertation. University of Massachusetts at Amherst.

    Google Scholar 

  13. R. G. Smith and R. Davis, “The Contract Net Protocol: High-Level Communication and Control in a Distributed Problem Solver,” in Transactions on Computers: IEEE, 1980, pp. 1104–1113.

    Google Scholar 

  14. Vickrey, W. (1961). Counter speculation, auctions, and competitive sealed tenders. Journal of Finance, 16:8–37.

    Google Scholar 

  15. Wellman M. P. (1994). Market-oriented programming: some early lessons. Department of Electrical Engineering and Computer Science, University of Michigan. Ann Arbor.

    Google Scholar 

  16. Zlotkin G., Rosenschein J. S. (1993). One, Two, Many: Coalitions in Multi-Agent Systems. Proceedings of the Fifth European Workshop on Modelling Autonomous Agents in a Multi-Agent World, Neuchatel, Switzerland.

    Google Scholar 

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Ernesto Coasta Amilcar Cardoso

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© 1997 Springer-Verlag Berlin Heidelberg

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Fonseca, J.M., de Oliveira, E., Steiger-Garção, A. (1997). Multi-agent negotiation algorithms for resources cost estimation: A case study. In: Coasta, E., Cardoso, A. (eds) Progress in Artificial Intelligence. EPIA 1997. Lecture Notes in Computer Science, vol 1323. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0023922

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  • DOI: https://doi.org/10.1007/BFb0023922

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63586-4

  • Online ISBN: 978-3-540-69605-6

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