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An Evolutionary Framework for Determining Heterogeneous Strategies in Multi-Agent Marketplaces

Author

Listed:
  • Babanov, A.
  • Ketter, W.
  • Gini, M.

Abstract

We propose an evolutionary approach for studying the dynamics of interaction of strategic agents that interact in a marketplace. The goal is to learn which agent strategies are most suited by observing the distribution of the agents that survive in the market over extended periods of time. We present experimental results from a simulated market, where multiple service providers compete for customers using different deployment and pricing schemes. The results show that heterogeneous strategies evolve and co-exist in the same market.

Suggested Citation

  • Babanov, A. & Ketter, W. & Gini, M., 2008. "An Evolutionary Framework for Determining Heterogeneous Strategies in Multi-Agent Marketplaces," ERIM Report Series Research in Management ERS-2008-002-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
  • Handle: RePEc:ems:eureri:10972
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    File URL: https://repub.eur.nl/pub/10972/ERS-2008-002-LIS.pdf
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    References listed on IDEAS

    as
    1. Alex Anas & Richard Arnott & Kenneth A. Small, 1998. "Urban Spatial Structure," Journal of Economic Literature, American Economic Association, vol. 36(3), pages 1426-1464, September.
    2. McFadzean, David & Stewart, Deron & Tesfatsion, Leigh, 2000. "A Computational Laboratory for Evolutionary Trade Network," ISU General Staff Papers 200008010700001051, Iowa State University, Department of Economics.
    3. Tesfatsion, Leigh S., 2002. "Agent-Based Computational Economics: Growing Economies from the Bottom Up," Staff General Research Papers Archive 5075, Iowa State University, Department of Economics.
    4. Edwin S. Mills & Michael R. Lav, 1964. "A Model of Market Areas with Free Entry," Journal of Political Economy, University of Chicago Press, vol. 72(3), pages 278-278.
    5. Alvin E. Roth, 2002. "The Economist as Engineer: Game Theory, Experimentation, and Computation as Tools for Design Economics," Econometrica, Econometric Society, vol. 70(4), pages 1341-1378, July.
    6. Richard R. Nelson, 1995. "Recent Evolutionary Theorizing about Economic Change," Journal of Economic Literature, American Economic Association, vol. 33(1), pages 48-90, March.
    7. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, April.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    complexity economics; marketing; multi-agent systems; simulation; trading agents;
    All these keywords.

    JEL classification:

    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality
    • M - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

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