A talk at the workshop on "Agent-Based Models in Philosophy: Prospects and Limitations", Workshop on Agent-Based Models in Philosophy, Rurh University, Bochum, Germany. March 2019
Abstract:
ABMs (like other kinds of model) can be used in a purely abstract
way, as a kind of thought experiment - a way of thinking about some
aspect of the world that is too complicated to hold in our mind (in all
its detail). In this way it both informs and complements discursive
thought. However there is another set of uses for ABMs - empirical uses -
where the mapping between the model and sets of observation-derived
data are crucial. For these uses, one has to (a) use the mapping to get
from some data to the model (b) use the model for some inference and (c)
use the mapping again back to data. This includes both predictive and
explanatory uses of ABMs. These are easily distinguishable from abstact
uses becuase there is a fixed and well-defined relationship between the
model and the data, this is not flexible on a case by case basis. In
these cases the reliability comes from the composite (a)-(b)-(c)
mapping, so that simplifying step (b) can be counterproductive if that
means weakening steps (a) and (c) because it is the strength of the
overall chain that is important. Taking the use of models in quantum
mechanics as an example, one can see that sometimes the evolution of the
formal models driven by empirical adequacy can be more important than
the attendent abstract models used to get a feel for what is happening.
Although using ABM's for empirical purposes is more challenging than for
purely abstract purposes, they are being increasingly used for
empirical explanation rather than thought experiments, and there is no
reason to suppose that robust empirical adequacy is unachievable.
Slides at: https://www.slideshare.net/BruceEdmonds/the-evolution-of-empirical-abms-137463946
