Many of the topics considered in the earlier chapters have to do with the relation between macro and micro, and social and individual. These topics are potentially relevant to a very lively body of work emerging within the interdisciplinary fields of complex systems, computational mathematics, and simulation studies. This emerging synergy between advanced computational mathematics and the social sciences is possible because of the way that social phenomena emerge from the actions and thoughts of individual actors in relationship to each other. This is what allows us to join simulation models to methodology and explanation. Essentially, we can think of the upward strut of Coleman’s boat (Figure 4.2)—the part of the story that has to do with the “aggregation dynamics” of a set of actors—and can try to create models that can serve to simulate the effects of these actions and interactions. A well- known example is Thomas Schelling’s simulation of residential segregation (Schelling 1971). This chapter will consider some of the philosophical and methodological issues that arise from this intersection.
As we have seen at many points already, apparently simple assumptions about the social world give rise to very different ideas about ontology and methodology. This is true for the current chapter as well. One group of scientists examines the tools of agent-based simulation and conclude that it should be possible to generate all important social phenomena making use of these tools. These are the advocates of “generativity.” Another group of scientists are struck by the unpredictability of complex systems and observe that complex systems have novel characteristics not found among the units. Complex systems possess features like “tight linkage,” “nonlinearity,” path dependence, and multiple systems of feedback that lead to dynamics that are difficult or impossible to predict, and leading complexity theorists argue that complex systems have “emergent” properties. These scientists are grouped ...
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