Compact Representations of Extended Causal Models
This work addresses a theoretical problem in causal inference for researchers, but it is incremental as it builds on prior definitions without introducing new paradigms.
The paper tackles the complexity of extended causal models, which combine causal structure and normality, by developing a method for their compact representation.
Judea Pearl was the first to propose a definition of actual causation using causal models. A number of authors have suggested that an adequate account of actual causation must appeal not only to causal structure, but also to considerations of normality. In earlier work, we provided a definition of actual causation using extended causal models, which include information about both causal structure and normality. Extended causal models are potentially very complex. In this paper, we show how it is possible to achieve a compact representation of extended causal models.