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ACE Models of Endogenous Interactions

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  • Nicolaas J. Vriend

    (Queen Mary, University of London)

Abstract

Various approaches used in Agent-based Computational Economics (ACE) to model endogenously determined interactions between agents are discussed. This concerns models in which agents not only (learn how to) play some (market or other) game, but also (learn to) decide with whom to do that (or not).

Suggested Citation

  • Nicolaas J. Vriend, 2005. "ACE Models of Endogenous Interactions," Working Papers 542, Queen Mary University of London, School of Economics and Finance.
    • Handle: RePEc:qmw:qmwecw:542
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    References listed on IDEAS

    as
    1. Kirman, Alan P. & Vriend, Nicolaas J., 2001. "Evolving market structure: An ACE model of price dispersion and loyalty," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 459-502, March.
    2. Ashlock, Dan & Smucker, Mark & Stanley, E. Ann & Tesfatsion, Leigh, 1994. "Preferential Partner Selection in an Evolutionary Study of Prisoner's Dilemma," ISU General Staff Papers 199409010700001033, Iowa State University, Department of Economics.
    3. Arthur, W Brian, 1994. "Inductive Reasoning and Bounded Rationality," American Economic Review, American Economic Association, vol. 84(2), pages 406-411, May.
    4. Pancs, Romans & Vriend, Nicolaas J., 2007. "Schelling's spatial proximity model of segregation revisited," Journal of Public Economics, Elsevier, vol. 91(1-2), pages 1-24, February.
    5. 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.
    6. Oechssler, Jorg, 1997. "Decentralization and the coordination problem," Journal of Economic Behavior & Organization, Elsevier, vol. 32(1), pages 119-135, January.
    7. Pancs, Romans & Vriend, Nicolaas J., 2007. "Schelling's spatial proximity model of segregation revisited," Journal of Public Economics, Elsevier, vol. 91(1-2), pages 1-24, February.
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    Citations

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    Cited by:

    1. Chang, Myong-Hun & Harrington, Joseph Jr., 2006. "Agent-Based Models of Organizations," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 26, pages 1273-1337, Elsevier.
    2. Haydée Lugo & Raúl Jiménez, 2006. "Incentives to Cooperate in Network Formation," Computational Economics, Springer;Society for Computational Economics, vol. 28(1), pages 15-27, August.
    3. 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.
    4. Jackson, Matthew O. & Zenou, Yves, 2015. "Games on Networks," Handbook of Game Theory with Economic Applications,, Elsevier.
    5. Dan Ladley & Seth Bullock, 2008. "The Strategic Exploitation of Limited Information and Opportunity in Networked Markets," Computational Economics, Springer;Society for Computational Economics, vol. 32(3), pages 295-315, October.
    6. Chad Seagren, 2011. "Examining social processes with agent-based models," The Review of Austrian Economics, Springer;Society for the Development of Austrian Economics, vol. 24(1), pages 1-17, March.
    7. Vivien Lespagnol & Juliette Rouchier, 2018. "Trading Volume and Price Distortion: An Agent-Based Model with Heterogenous Knowledge of Fundamentals," Post-Print hal-02084910, HAL.
    8. Karolina Safarzyńska & Jeroen Bergh, 2010. "Evolutionary models in economics: a survey of methods and building blocks," Journal of Evolutionary Economics, Springer, vol. 20(3), pages 329-373, June.
    9. Vivien Lespagnol & Juliette Rouchier, 2018. "Trading Volume and Price Distortion: An Agent-Based Model with Heterogenous Knowledge of Fundamentals," Computational Economics, Springer;Society for Computational Economics, vol. 51(4), pages 991-1020, April.
    10. Narine Udumyan & Juliette Rouchier & Dominique Ami, 2014. "Integration of Path-Dependency in a Simple Learning Model: The Case of Marine Resources," Computational Economics, Springer;Society for Computational Economics, vol. 43(2), pages 199-231, February.
    11. Jack Robles, 2008. "Evolution, bargaining, and time preferences," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 35(1), pages 19-36, April.
    12. Wilhite, Allen, 2014. "Network structure, games, and agent dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 47(C), pages 225-238.
    13. Bargigli, Leonardo & Tedeschi, Gabriele, 2014. "Interaction in agent-based economics: A survey on the network approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 399(C), pages 1-15.
    14. Juliette Rouchier, 2013. "The Interest of Having Loyal Buyers in a Perishable Market," Computational Economics, Springer;Society for Computational Economics, vol. 41(2), pages 151-170, February.

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    More about this item

    Keywords

    Endogenous interaction; Agent-based Computational Economics (ACE);

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C7 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory
    • D1 - Microeconomics - - Household Behavior
    • D2 - Microeconomics - - Production and Organizations
    • D3 - Microeconomics - - Distribution
    • D4 - Microeconomics - - Market Structure, Pricing, and Design
    • D5 - Microeconomics - - General Equilibrium and Disequilibrium
    • D6 - Microeconomics - - Welfare Economics
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance
    • M3 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising

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