Thinking Outside the Box: A Critical Evaluation of Oblique Decision Tree Algorithms for Scenario Discovery
J.T. ter Horst (TU Delft - Technology, Policy and Management)
Jan H. Kwakkel – Graduation committee member (TU Delft - Policy Analysis)
Martijn Warnier – Graduation committee member (TU Delft - Multi Actor Systems)
P. Steinmann – Mentor (TU Delft - Technology, Policy and Management)
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Abstract
In an era shaped by systemic risks and long-term challenges such as climate change, technological disruption and geopolitical instability, policymakers must make consequential decisions without knowing what the future holds. This condition, known as deep uncertainty, arises when the relationships between actions and outcomes are contested and traditional prediction methods no longer apply. To address this, analysts have turned to computational tools such as scenario discovery, which explores thousands of simulated futures to identify combinations of factors that lead to policy success or failure. It provides decision-makers with understandable scenarios: data-grounded narratives of the future that highlight critical vulnerabilities and opportunities. These scenarios help enable the design of strategies that are robust and adaptive...