A Markov kernel (also called transition kernel, stochastic kernel, or probability kernel) describes a random state transition or other forms of stochastic dependence by assigning to each input a probability law for the possible outputs. (Sometimes the term transition kernel denotes a more general, non-normalized mapping.) It can be thought of as a generalization of a stochastic map outside the finite discrete case. (Sometimes the term “stochastic map” is itself used to denote a Markov...