  The premise of this working paper is based around agent-based simulation
models and how to go about creating them from given incomplete information.
Agent-based simulations are stochastic simulations that revolve around groups
of agents that each have their own characteristics and can make decisions. Such
simulations can be used to emulate real life situations and to create
hypothetical situations without the need for real-world testing prior. Here we
describe the development of an agent-based simulation model for studying future
digital mental health scenarios. An incomplete conceptual model has been used
as the basis for this development. To define differences in responses to
stimuli we employed fuzzy decision making logic. The model has been implemented
but not been used for structured experimentation yet. This is planned as our
next step.
