The Logical Essentials of Bayesian Reasoning
  This chapter offers an accessible introduction to the channel-based approach
to Bayesian probability theory. This framework rests on algebraic and logical
foundations, inspired by the methodologies of programming language semantics.
It offers a uniform, structured and expressive language for describing Bayesian
phenomena in terms of familiar programming concepts, like channel, predicate
transformation and state transformation. The introduction also covers inference
in Bayesian networks, which will be modelled by a suitable calculus of string
diagrams.
