  In this article, we review a general theoretical framework of thermodynamics
of information on the basis of Bayesian networks. This framework can describe a
broad class of nonequilibrium dynamics of multiple interacting systems with
complex information exchanges. For such situations, we discuss a generalization
of the second law of thermodynamics including information contents. The key
concept here is an informational quantity called the transfer entropy, which
describes the directional information transfer in stochastic dynamics. The
generalized second law gives the fundamental lower bound of the entropy
production in nonequilibrium dynamics, and sheds modern light on the paradox of
"Maxwell's demon" that performs measurements and feedback control at the level
of thermal fluctuations.
