Chris Goldspink (2002)
Methodological Implications Of Complex Systems Approaches to Sociality: Simulation as a foundation for knowledge
Journal of Artificial Societies and Social
vol. 5, no. 1
To cite articles published in the Journal of Artificial Societies and Social
Simulation, please reference the above information and include paragraph
numbers if necessary
To cite articles published in the Journal of Artificial Societies and Social Simulation, please reference the above information and include paragraph numbers if necessary
A computer is an organization of elementary functional components in which, to a high approximation, only the function performed by those components is relevant to the behavior of the whole system (1996: 17-18).
Like deduction, it starts with a set of explicit assumptions. But unlike deduction, it does not prove theorems. Instead simulation generates data that can be analysed inductively. Unlike typical induction, however, the simulated data comes from a specified set of rules rather than direct measurement of the real world (1997: 17).
If sensitivity analysis has yielded the result that the trajectory of the system depends sensitively on initial conditions and parameters, then quantitative prediction may not be possible at all. And if the model is stochastic, then only a prediction in probability is possible (1997: 49).
We can't know what will happen regardless of our acts. We can know what might happen if we act a certain way... In this way of thinking simulation is clearly a tool which helps us not know what will happen, but what can be made to happen (1997: 5).
|Figure 1. McKelvey's (1999) conception of the Axiom-theory-model- phenomena relationship.|
ontological adequacy is tested by comparing the isomorphism of the models idealised structures/processes against that portion of the total "real-world" phenomena defined as "within scope of the theory (1999: 18).
|Figure 2. An extended semantic model.|
Qualitative descriptions seem to be best suited for capturing the circular texture of organisational phenomena. How else could one hope to do justice to the historicity of the phenomena to be explained, if not by narrating how the actions of interacting agents and the occurrence of chance events, unfolding in time, have been intertwined to generate the phenomena at hand (1998: 303).
Narratives are analytical constructs that unify a number of past or contemporaneous actions and happenings, which might otherwise have been viewed as discrete or disparate, into coherent relational whole that gives meaning to and explains each of its elements (1993: 1097).
if puny and unknowable details do in fact play an essential role in some particular history, narrative accounts of that history need not have access to that detail. The narrator can still describe and emplot events and the effects of that detail even though the detail itself and its causal power is not recognised. As a causal explanation the resulting narrative would appear, from some ideal vantage, to be incomplete or incorrect. But at least it would remain parallel and in step with events that actually occurred (1991: 18).
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