Abstract
The effects of distinct agent interaction and activation structures are compared and contrasted in several multi-agent models of social phenomena. Random graphs and lattices represent two limiting kinds of agent interaction networks studied, with so-called ‘small-world’ networks being an intermediate form between these two extremes. A model of retirement behavior is studied with each network type, resulting in important differences in key model outputs. Then, in the context of a model of multi-agent firm formation it is demonstrated that the medium of interaction‐whether through individual agents or through firms‐affects the qualitative character of the results. Finally, alternative agent activation ‘schedules’ are studied. In particular, two activation modes are compared: (1) all agents being active exactly once each period, and (2) each agent having a random number of activations per period with mean 1. In some models these two regimes produce indistinguishable results at the aggregate level, but in certain cases the differences between them are significant.
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References
Aaron, H., ed. 1999. Behavioral Dimensions of Retirement Economics.Russell Sage Foundation/ Brookings Institution Press: New York/ Washington, D.C.
Axelrod, R. 1997. “The Dissemination of Culture: A Model with Local Convergence and Global Polarization.” Journal of Conflict Resolution, 41: 203–226.
Axtell, R.L. 1999. “The Emergence of Firms in a Population of Agents: Local Increasing Returns, Unstable Nash Equilibria, and Power Law Size Distributions.” Working paper 03-019-99. Santa Fe Institute: Santa Fe, N.M. Available at http://www.brook.edu/es/dynamics/papers.
Axtell, R.L., R. Axelrod, J.M. Epstein and M.D. Cohen. 1996. “Aligning Simulation Models: A Case Study and Results.” Computational and Mathematical Organization Theory, 1(2):123–41.
Axtell, R.L. and J.M. Epstein. 1999. “Coordination in Transient Social Networks: An Agent-Based Computational Model of the Timing of Retirement.” In Aaron, ed. [1]. Available in working paper form at http://www.brook.edu/es/dynamics/papers.
Bollobás, B. 1979. Graph Theory. Springer-Verlag: N.Y.
Ellison, G. 1993. “Learning, Local Interaction, and Coordination.” Econometrica, 61: 1047–71.
Epstein, J.M. and R. Axtell. 1996. Growing Artificial Societies: Social Science from the Bottom Up. MIT Press/Brookings Institution Press: Cambridge, Mass./Washington, D.C.
Gács, P. 1997. “Deterministic Computations whose History is Independent of the Order of Asynchronous Updating.” Working paper. Boston Univ.: Boston, Mass.
Huberman, B.A. and N.S. Glance. 1993. “Evolutionary Games and Computer Simulations.” Proceedings of the National Academy of Sciences USA, 90: 7716–18.
Kochen, M., ed. 1989. The Small World. Ablex Publishing Corporation: Norwood, N.J.
Page, S.E. 1997. “On Incentives and Updating in Agent Based Models.” Computational Economics, 10 (1): 67–87.
Page, S.E. 1999. “Network Structure Matters.” Working paper. Department of Political Science. University of Michigan.
Rubinstein, A. 1998. Modeling Bounded Rationality. MIT Press: Cambridge, Mass.
Simon, H.A. 1998. In Rubinstein [14].
Watts, D. 1999. Small Worlds: The Dynamics of Networks Between Order and Randomness. Princeton University Press: Princeton, N.J.
Watts, D.J. and S.H. Strogatz. 1998. “Collective Dynamics of Small-World Networks.” Nature, 393: 440–442.
Wei\, G., ed. 1998. Multi-Agent Systems. MIT Press: Cambridge, Mass.
Young, H.P. 1998. Individual Strategy and Social Structure. Princeton University Press: Princeton, N.J.
Young, H.P. 1999. Diffusion in Social Networks. Center on Social and Economic Dynamics working paper. Brookings Institution: Washington, D.C. Available at http://www.brook.edu/es/dynamics/papers.
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Axtell, R. (2000). Effects of Interaction Topology and Activation Regime in Several Multi-Agent Systems. In: Moss, S., Davidsson, P. (eds) Multi-Agent-Based Simulation. MABS 2000. Lecture Notes in Computer Science(), vol 1979. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44561-7_3
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DOI: https://doi.org/10.1007/3-540-44561-7_3
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