FACULTY OF TECHNOLOGY AND SOCIETY | Seminar
Licentiate seminar – Michael Belfrage

This dissertation explores the use of Agent-based Social Simulation (ABSS) and policy-modelling to support policy-making. ABSS, consisting of autonomous agents mimicking human behavior, offers a valuable alternative to traditional policy analysis methods by employing agent technology in the exploration of complex social systems and emerging behaviors. This approach allows policy-makers to perform simulated policy experiments in a safe digital environment, assessing potential adverse effects before implementation. Despite its potential, ABSS adoption in policy-making is limited. The main purpose of the dissertation is to better understand why this is the case and how the current challenges can be addressed to increase ABSS usage in policy-making.
Using a systematic review approach, six challenges in applied policy-modelling were identified: scope, politics, management, understandability, credibility, and data. It shows that upstream modelling decisions affect the rigor of model testing and highlights trans-parency issues like those prevalent during the COVID-19 pandemic. Furthermore, the dissertation highlights that the lack of formal accreditation and communication of model results poses a significant risk for faulty applications, which can cause societal harm. Ad-dressing this weakness in the application-chain to increase the robustness of evidence-based policymaking is of the utmost importance.
Using a design science methodology, two artifacts were developed to address these challenges. The first includes a verification and validation protocol and an accreditation framework, facilitating independent credibility assessment of ABSS models. This design aligns model application with the scientific principle of independent review and strength-ens the application-chain through quality assurance prior to application. The second arti-fact is a high-fidelity policy-modelling methodology employing the Institutional Grammar 2.0, ensuring systematic and transparent modelling using the case of organ donation. This methodology formalizes implemented regulations before involving subject matter experts, ensuring methodological stringency for the development of policy models. These artifacts seek to contribute to the development of realistic policy models and their responsible de-ployment as decision support tools within the public sector.