This open access book presents a ground-breaking approach to developing micro-foundations for
demography and migration studies. It offers a unique and novel methodology for creating
empirically grounded agent-based models of international migration - one of the most uncertain
population processes and a top-priority policy area. The book discusses in detail the process
of building a simulation model of migration based on a population of intelligent cognitive
agents their networks and institutions all interacting with one another. The proposed
model-based approach integrates behavioural and social theory with formal modelling by
embedding the interdisciplinary modelling process within a wider inductive framework based on
the Bayesian statistical reasoning. Principles of uncertainty quantification are used to devise
innovative computer-based simulations and to learn about modelling the simulated individuals
and the way they make decisions. The identified knowledge gaps are subsequently filled with
information from dedicated laboratory experiments on cognitive aspects of human decision-making
under uncertainty. In this way the models are built iteratively from the bottom up filling
an important epistemological gap in migration studies and social sciences more broadly.
