Abstract
It is argued that three distinct uses of agent-based
computational models exist in the social sciences. Only one such
use - the simplest - deserves to be called simulation. This use
arises when equations can be formulated that completely describe
a social process, and these equations are explicitly soluble,
either analytically or numerically. In the former case, the agent
model is merely a tool for presenting results, while in the
latter it is novel kind of Monte Carlo analysis. A second, more
commonplace usage of computational agent models arises when
equations can be written down but not be completely solved. In
this case the agent-based model can shed significant light on the
solution structure, illustrate dynamical properties of the model,
serve to test the dependence of results on parameters and
assumptions, and be a source of counter-examples. Finally, there
are important classes of problems for which writing down
equations is not a useful activity. In such circumstances resort
to agent-based computational models may be the only way available
to explore such processes systematically, and constitute a third
distinct usage of such models.
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