Agent-Based Simulation Modelling for Reflecting on Consequences of Digital Mental Health

TL;DR

This paper discusses the development of an agent-based simulation model using fuzzy logic to explore future digital mental health scenarios, emphasizing the creation process from incomplete information.

Contribution

It introduces a novel approach to building agent-based models for digital mental health using fuzzy decision-making with incomplete data.

Findings

Model has been implemented successfully.

Framework for simulating digital mental health scenarios.

Next step: structured experimentation planned.

Abstract

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.