The introduction to Growing Artificial Societies offers the following
thought on the future of explanation:
What constitutes an explanation of an observed social phenomenon? Perhaps
one day people will interpret the question, “Can you explain it?” as asking,
“Can you grow it?” Artificial society modeling allows us to “grow”
social structures in silico demonstrating that certain sets of
microspecifications are sufficient to generate the macrophenomena
of interest … We can, of course, use statistics to test the match between
the true, observed, structures and the ones we grow. But the ability to
grow them … is what is new. Indeed, it holds out to prospect of a new, generative, kind
of social science.
A concluding section of the same work, entitled “Generative Social Science,”
restates the point even more broadly:
In effect, we are proposing a generative program for the social sciences
and see the artificial society as its principle instrument.” (p. xi) ----
“Many important social processes are not neatly
decomposable into separate subprocesses --- economic, demographic, cultural,
spatial --- whose isolated analysis can be somehow ‘aggregated’ to yield
an adequate analysis of the process as whole. Yet this is exactly how academic
social science is organized --- into more or less insular departments and
journals of economics, demography, anthropology, and so on. While many
social scientists would agree that these divisions are artificial, they
would argue that there is no ‘natural methodology’ for studying these processes
together, as they interact, though attempts have been made. Social scientists
have taken highly aggregated mathematical models --- of entire national
economies, political systems, and so on --- and have ‘connected’ them yielding
‘mega-models that have been attacked on several grounds ---. But attacks
on specific models have had the effect of discrediting interdisciplinary
inquiry itself, and this is most unfortunate. The line of inquiry remains
crucially important. And agent-based modeling offers an alternative, and
very natural technique. (p. 18)
— “The motto, in short, is: If you didn’t grow it, you didn’t explain it.” (p. 51)
Epstein, Joshua M., Generative Social Science: Studies in Agent-Based Computational Modeling, Princeton University Press 2006.