Agent-Based Modeling Workshop: December 10-11, 2018

** This workshop is by invitation only **


This workshop will be held at Gross Hall on the campus of Duke University.


Agent-based modeling is widely used across many disciplines to study
complex emergent behavior generated from simulated entities that
interact with each other and their environment according to relatively
simple rules. Applications include automobile traffic modeling, weather
forecasting, and the study of epidemics. The inferential challenge of
agent-based models is that (in general) there is no tractable likelihood
function, and thus it is difficult to fit the model or make quantified
statements about the accuracy of predictions. This workshop addresses
that challenge from the perspective of uncertainty quantification, so
that emulator methodology can be used to make approximate principled
inferences about agent-based simulations.

Questions: email