Human decision making for empirical agent-based models: construction and validation

Results from agent-based or multi-agent simulation (AB/MAS) modelling
can provide relevant information for policy makers, scientists and stakeholders
about the boundary conditions of rural development and the uncertainties involved
in land-use/cover change (LUCC). However, the process of model validation that
can build trust in the outcomes for new parameter conditions and in future
scenarios is not a trivial problem. Apparently, no common measure of the degree of
confounding between parameterization and validation data sets exists. The current
lack of success and the effort necessary for validating the models can be traced to
the weak theoretical representation of human decision making in current models.
Thus, this paper reviews various ways to represent land-use decision making using
AB/MAS models. It briefly describes process-based decision making as an
alternative approach to address the problem of weak theoretical representation of
human decision making, and presents a case study of an agent decision-making
model applying an empirical validation technique.