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Canonical Tasks, Environments and Models for Social Simulation

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  • Scott Moss

    (Manchester Metropolitan University)

Abstract

The purpose of this paper is to propose and describe an alternative to an overarching theory for social simulation research. The approach is an analogy of the canonical matrix. Canonical matrices are matrices of a standard form and there are transformations that can be performed on other matrices to show that they can be made into canonical matrices. All matrices which, by means of allowable operations, can be transformed into a canonical matrix have the properties of the canonical matrix. This conception of canonicity is applied to three models in the computational organization theory literature. The models are mapped into their respective canonical forms. The canonical forms are shown to be transitively subsumptive (i.e., one of them is “nested” within a second which itself is “nested” within the third. The consequences of these subsumption relations are investigated by means of simulation experiments.

Suggested Citation

  • Scott Moss, 2000. "Canonical Tasks, Environments and Models for Social Simulation," Computational and Mathematical Organization Theory, Springer, vol. 6(3), pages 249-275, September.
    • Handle: RePEc:spr:comaot:v:6:y:2000:i:3:d:10.1023_a:1009629602618
    DOI: 10.1023/A:1009629602618
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    References listed on IDEAS

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    1. Scott Moss & Helen Gaylard & Steve Wallis & Bruce Edmonds, 1998. "SDML: A Multi-Agent Language for Organizational Modelling," Computational and Mathematical Organization Theory, Springer, vol. 4(1), pages 43-69, March.
    2. Scott Moss, 1998. "Critical Incident Management: an Empirically Derived Computational Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 1(4), pages 1-1.
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    Cited by:

    1. Uri Wilensky & William Rand, 2007. "Making Models Match: Replicating an Agent-Based Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(4), pages 1-2.

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