An extension of the concept of a Markov Normal Algorithm (not to be confused with Markov Probabilistic Processes) is introduced as a basis for a universal constructive theory of discrete probabilistic processes, including basics single sequential processes, also sets of parallel concurrent processes. The concept of a probabilistic Markov Algorithm can in fact be considered as a universal theory of effective discrete probabilistic processes. Moreover sets of a Markov Normal Algorithms to be simultaneously applied to a common string can be considered as a basic model for sets of discrete parallel concurrent processes. A stocastic selection for incompatibilities gives rise to a global probabilistic process and a preliminary investigation is performed concerning the relation between probabilistic Markov Algorithms and incompatible sets of Markov Normal Algorithm.
