Distributed Self-Organizing Migrating Algorithm and Evolutionary Scanning

neural network, symbolic regression, analytic programming, evolutionary searching, evolutionary scanning, evolutionary algorithms, distributed computing 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