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A Landscape Theory of Aggregation

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  • Axelrod, Robert
  • Bennett, D. Scott

Abstract

Aggregation means the organization of elements of a system into patterns that tend to put highly compatible elements together and less compatible elements apart. Landscape theory Predicts how aggregation will lead to alignments among actors (such as nations), whose leaders are myopic in their assessments and incremental in their actions. The predicted configurations are based upon the attempts of actors to minimize their frustration based upon their pairwise Propensities to align with some actors and oppose others. These attempts lead to a local minimum in the energy landscape of the entire system. The theory is supported by the results of two cases: the alignment of seventeen European nations in the Second World War and membership in competing alliances of nine computer companies to set standards for Unix computer operating systems. The theory has potential for application to coalitions of political Parties in parliaments, social networks, social cleavages in democracies and organizational structures.

Suggested Citation

  • Axelrod, Robert & Bennett, D. Scott, 1993. "A Landscape Theory of Aggregation," British Journal of Political Science, Cambridge University Press, vol. 23(2), pages 211-233, April.
    • Handle: RePEc:cup:bjposi:v:23:y:1993:i:02:p:211-233_00
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    17. Arabzadeh, S. & Sherafati, M. & Atyabi, F. & Jafari, G.R. & Kułakowski, K., 2021. "Lifetime of links influences the evolution towards structural balance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
    18. Claudio Cioffi-Revilla, 2009. "Simplicity and reality in computational modeling of politics," Computational and Mathematical Organization Theory, Springer, vol. 15(1), pages 26-46, March.
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    22. Pierpaolo Andriani & Bill McKelvey, 2006. "Beyond Gaussian Averages: Redirecting Management Research Toward Extreme Events and Power Laws," Department of Economics Working Papers 2006_03, Durham University, Department of Economics.
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    24. Hedayatifar, L. & Hassanibesheli, F. & Shirazi, A.H. & Vasheghani Farahani, S. & Jafari, G.R., 2017. "Pseudo paths towards minimum energy states in network dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 109-116.
    25. Musatov, Daniil & Savvateev, Alexei & Weber, Shlomo, 2016. "Gale–Nikaido–Debreu and Milgrom–Shannon: Communal interactions with endogenous community structures," Journal of Economic Theory, Elsevier, vol. 166(C), pages 282-303.

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