Actual causality in fault trees
Georgiana Caltais, Milan Lopuhaä-Zwakenberg, Mariëlle Stoelinga
cs.AI
Abstract
Fault trees are a widely used as effective risk models for complex systems, answering the question "what can go wrong?", especially through minimal cut set analysis. We study fault trees from the perspective of Halpern & Pearl's theory of actual causality. This allows us to use fault trees to answer the question "why has it gone wrong?", which is fundamental to failure diagnostics. We give a complete classification of each of the different notions of actual causality in terms of the fault tree's graph structure and logical structure, and show how minimal cut sets give rise to actual causes.
Topics
Classified with taxonomy v2 on Wed, 2 Sept 2026.