[In case it���s helpful, to illustrate the level of question I want to be able ask, here is the question with which I���m currently struggling: I���m reading Hermans and Skulj���s ���Stochastic processes��� chapter of of Introduction to Imprecise Probabilities, and I���m puzzled by the novel (to me) definition of ���transition operator��� in 11.3.  I understand that it���s intended as a sort of generalization of the standard Markov process transition operator concept, but there���s something I���m just not seeing due to lack of experience, lack of insight, etc.:  As I understand definition 11.3, T_n f(x) is essentially a conditional expectation���i.e., in traditional notation: E( f | X_n = x).    How is it that T_n can operate on f(x) and ���see��� what x is?  Either I must take 11.3 to imply that the domain of T_n consists of the range of f, or that the domain of T_n consists of gambles f in L(X_n).  Either way, x does not seem to appear as an argument to T_n; it seems to ���know��� nothing about x.  If the first interpretation were correct, then if f was not one-to-one, f(x) could equal f(y) where x != y, and I see no reason to assume that E(f | X_n=x) must always equal E(f | X_n=y).  I���m not sure if I���m making myself clear; I���m sure that there���s something I've overlooked, or that I���m misinterpreting some notation or concept.]