IDEAS home Printed from https://ideas.repec.org/a/aea/jecper/v9y1995i1p141-52.html
   My bibliography  Save this article

Distributed Computation as an Economic System

Author

Listed:
  • Bernardo A. Huberman
  • Tad Hogg

Abstract

As computer networks grow and blanket the planet, they become a community of concurrent processes, which, in their interactions, strategies, and lack of perfect knowledge, become analogous to human market economies. Economics may thus offer new ways of designing and understanding the behavior of distributed computer systems.

Suggested Citation

  • Bernardo A. Huberman & Tad Hogg, 1995. "Distributed Computation as an Economic System," Journal of Economic Perspectives, American Economic Association, vol. 9(1), pages 141-152, Winter.
  • Handle: RePEc:aea:jecper:v:9:y:1995:i:1:p:141-52
    Note: DOI: 10.1257/jep.9.1.141
    as

    Download full text from publisher

    File URL: http://www.aeaweb.org/articles.php?doi=10.1257/jep.9.1.141
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rust, John & Miller, John H. & Palmer, Richard, 1994. "Characterizing effective trading strategies : Insights from a computerized double auction tournament," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 61-96, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Nisan, Noam & Ronen, Amir, 2001. "Algorithmic Mechanism Design," Games and Economic Behavior, Elsevier, vol. 35(1-2), pages 166-196, April.
    2. Karla Atkins & Achla Marathe & Chris Barrett, 2007. "A computational approach to modeling commodity markets," Computational Economics, Springer;Society for Computational Economics, vol. 30(2), pages 125-142, September.
    3. Ben-David, Shaul & Brookshire, David S. & Burness, Stuart & McKee, Michael & Schmidt, Christian, 1999. "Heterogeneity, Irreversible Production Choices, and Efficiency in Emission Permit Markets," Journal of Environmental Economics and Management, Elsevier, vol. 38(2), pages 176-194, September.
    4. Dale O. Stahl, 2002. "The Inefficiency of First and Second Price Auctions in Dynamic Stochastic Environments," Netnomics, Springer, vol. 4(1), pages 1-18, March.
    5. Mie Augier & Thorbjørn Knudsen, 2012. "The Architecture and Management of Knowledge in Organizations," Chapters, in: Richard Arena & Agnès Festré & Nathalie Lazaric (ed.), Handbook of Knowledge and Economics, chapter 19, Edward Elgar Publishing.
    6. T. Hogg & B. A. Huberman & M. Youssefmir, "undated". "The Instability of Markets," Working Papers _006, Xerox Research Park.
    7. Friedman, Eric & Shor, Mikhael & Shenker, Scott & Sopher, Barry, 2004. "An experiment on learning with limited information: nonconvergence, experimentation cascades, and the advantage of being slow," Games and Economic Behavior, Elsevier, vol. 47(2), pages 325-352, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Leigh Tesfatsion, 2002. "Agent-Based Computational Economics," Computational Economics 0203001, University Library of Munich, Germany, revised 15 Aug 2002.
    2. Zhan, Wenjie & Friedman, Daniel, 2007. "Markups in double auction markets," Journal of Economic Dynamics and Control, Elsevier, vol. 31(9), pages 2984-3005, September.
    3. Carsten Schmidt & Jens Grossklags, 2004. "Interaction of Human and Artificial Agents on Double Auction Markets - Simulations and Laboratory Experiments," Papers on Strategic Interaction 2003-22, Max Planck Institute of Economics, Strategic Interaction Group.
    4. Shira Fano & Paolo Pellizzari, 2011. "Time-Dependent Trading Strategies in a Continuous Double Auction," Lecture Notes in Economics and Mathematical Systems, in: Sjoukje Osinga & Gert Jan Hofstede & Tim Verwaart (ed.), Emergent Results of Artificial Economics, pages 165-176, Springer.
    5. Chen, Shu-Heng, 2012. "Varieties of agents in agent-based computational economics: A historical and an interdisciplinary perspective," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 1-25.
    6. Karla Atkins & Achla Marathe & Chris Barrett, 2007. "A computational approach to modeling commodity markets," Computational Economics, Springer;Society for Computational Economics, vol. 30(2), pages 125-142, September.
    7. Shu-Heng Chen & Tina Yu, 2011. "Toward an Autonomous-Agents Inspired Economic Analysis," ASSRU Discussion Papers 1118, ASSRU - Algorithmic Social Science Research Unit.
    8. Großklags, Jens & Schmidt, Carsten & Siegel, Jonathan, 2000. "Dumb software agents on an experimental asset market," SFB 373 Discussion Papers 2000,96, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    9. Bullard, James & Duffy, John, 1998. "A model of learning and emulation with artificial adaptive agents," Journal of Economic Dynamics and Control, Elsevier, vol. 22(2), pages 179-207, February.
    10. Matteo Richiardi & Roberto Leombruni & Nicole J. Saam & Michele Sonnessa, 2006. "A Common Protocol for Agent-Based Social Simulation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 9(1), pages 1-15.
    11. James Nicolaisen & Valentin Petrov & Leigh Tesfatsion, 2000. "Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing," Computational Economics 0004005, University Library of Munich, Germany.
    12. Jens Grossklags & Carsten Schmidt, 2002. "Artificial Software Agents on Thin Double Auction Markets - A Human Trader Experiment," Papers on Strategic Interaction 2002-45, Max Planck Institute of Economics, Strategic Interaction Group.
    13. Miller, John H. & Tumminello, Michele, 2015. "Bazaar economics," Journal of Economic Behavior & Organization, Elsevier, vol. 119(C), pages 163-181.
    14. Shu-Heng Chen & Chung-Ching Tai, 2006. "Republication: On the Selection of Adaptive Algorithms in ABM: A Computational-Equivalence Approach," Computational Economics, Springer;Society for Computational Economics, vol. 28(4), pages 313-331, November.
    15. Tai, Chung-Ching & Chen, Shu-Heng & Yang, Lee-Xieng, 2018. "Cognitive ability and earnings performance: Evidence from double auction market experiments," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 409-440.
    16. Henry Hanifan & Ben Watson & John Cartlidge & Dave Cliff, 2021. "Time Matters: Exploring the Effects of Urgency and Reaction Speed in Automated Traders," Papers 2103.00600, arXiv.org.
    17. Wurman, Peter R. & Wellman, Michael P. & Walsh, William E., 2001. "A Parametrization of the Auction Design Space," Games and Economic Behavior, Elsevier, vol. 35(1-2), pages 304-338, April.
    18. Shu-Heng Chen & Chung-Ching Tai, 2006. "On the Selection of Adaptive Algorithms in ABM: A Computational-Equivalence Approach," Computational Economics, Springer;Society for Computational Economics, vol. 28(1), pages 51-69, August.
    19. Te Bao & Elizaveta Nekrasova & Tibor Neugebauer & Yohanes E. Riyanto, 2022. "Algorithmic trading in experimental markets with human traders: A literature survey," Chapters, in: Sascha Füllbrunn & Ernan Haruvy (ed.), Handbook of Experimental Finance, chapter 23, pages 302-322, Edward Elgar Publishing.

    More about this item

    JEL classification:

    • L96 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Telecommunications
    • A14 - General Economics and Teaching - - General Economics - - - Sociology of Economics

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aea:jecper:v:9:y:1995:i:1:p:141-52. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Michael P. Albert (email available below). General contact details of provider: https://edirc.repec.org/data/aeaaaea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.