  Intervention theories of causality define a relationship as causal if
appropriately specified interventions to manipulate a putative cause tend to
produce changes in the putative effect. Interventionist causal theories are
commonly formalized by using directed graphs to represent causal relationships,
local probability models to quantify the relationship between cause and effect,
and a special kind of conditioning operator to represent the effects of
interventions. Such a formal model represents a family of joint probability
distributions, one for each allowable intervention policy. This paper
interprets the von Neumann formalization of quantum theory as an
interventionist theory of causality, describes its relationship to
interventionist theories popular in the artificial intelligence literature, and
presents a new family of graphical models that extends causal Bayesian networks
to quantum systems.
