  This paper presents a quantum version of the Monty Hall problem based upon
the quantum inferring acausal structures, which can be identified with
generalization of Bayesian networks. Considered structures are expressed in
formalism of quantum information theory, where density operators are identified
with quantum generalization of probability distributions. Conditional relations
between quantum counterpart of random variables are described by quantum
conditional operators. Presented quantum inferring structures are used to
construct a model inspired by scenario of well-known Monty Hall game, where we
show the differences between classical and quantum Bayesian reasoning.
