The authors of the present paper prepared a series of research related to the ways of representation by Generalized nets (GNs, see [1] and the Appendix) the process of machine learning of different objects, e,g" neural networks, genetic algorithms, GNs, expert systems, systems (abstract, statical, dynamical, stohastical and others), etc. Working on their research [21, where they gave a counterexample of the 62-nd Smarandachejs problem (see [3]), they saw that the process of the machine learning of the process of the mathematical problems solving also can be described by a GN and by this reason the result form [2] was used as an example of the present research. After this, they saw that the process of solving of a lot of the Smarandache's problems can be represented by GNs in a similar way and this will be an object of next their research.