Analytic Programming Powered by Distributed Self-Organizing Migrating Algorithm Application

This paper presents an idea of new algorithm combining advantages of evolutionary algorithm and simple distributed computing to perform tasks which required many re-runs of the same program. Computing time is shorted due to elementary distribution within a number of common computers via the Internet. Progressive .NET framework technology allowing this algorithm to run effectively and examples of possible usage are also described. The algorithm deals with a problem of synthesis of the artificial neural networks using the evolutional scanning method. The basic task to be solved is to create a symbolic regression algorithm on principles of analytic programming, which will be capable of performing a convenient neural network synthesis. The main motivation here is the computerization of such synthesis and discovering so far unknown solutions.