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ACE Models of Endogenous Interactions

In: Handbook of Computational Economics

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  • Vriend, Nicolaas J.

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

  • Vriend, Nicolaas J., 2006. "ACE Models of Endogenous Interactions," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 21, pages 1047-1079, Elsevier.
    • Handle: RePEc:eee:hecchp:v:2-21
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    Cited by:

    1. Jackson, Matthew O. & Zenou, Yves, 2015. "Games on Networks," Handbook of Game Theory with Economic Applications,, Elsevier.
    2. 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.
    3. Wilhite, Allen, 2014. "Network structure, games, and agent dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 47(C), pages 225-238.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.

    More about this item

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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