Proefschrift

From Inference to Influence: Applying Causal Game Theory to Complex Security Environments

Effective policy-making requires understanding what truly causes a problem. Only then can policymakers develop targeted interventions that achieve desired outcomes.

Auteur

M.C. Vonk

Datum

26 maart 2026

Links

Thesis in Leiden Repository

However, establishing causal relationships is challenging, as observed patterns do not automatically indicate true cause-and-effect.This thesis provides tools for applying causal analysis to complex security environments. What distinguishes these methods is their consideration of how different parties react to one another. Countries, organizations, and groups anticipate each other's actions and adapt accordingly.The thesis presents a structured framework supporting policymakers in selecting appropriate analytical methods for specific policy questions. It explains the necessary assumptions for each method alongside practical implementation guidance, and demonstrates how causal analysis can incorporate the intentions and reactions of adversaries.A key methodological innovation is an automated method for identifying optimal intervention points. Policymakers specify desired objectives, after which algorithms determine which interventions are most effective and how relevant variables should be adjusted.Practical applicability is demonstrated through two current security challenges: hybrid threats and climate-related conflicts, both characterized by uncertainty, multiple strategic actors, and mutual dependencies.The research produces an analytical toolkit for decision-making in complex security environments, facilitating more informed policy choices while building the analytical capabilities needed to navigate contemporary security challenges.

• bayesian networks
• causal discovery
• causal game theory
• causal inference
• conflict studies
• environmental conflict
• game theory
• hybrid threats