Automated generation of programs for a class of parametric neuroevolution algorithms

The facilities of algebra hyperschemes are applied for automated generation neuroevolution algorithms on an example a binary multiplexer evaluation problem, which is part the SharpNEAT system. open-source framework developed in C# programming language, implements genetic algorithm .NET platform. Neuroevolution form artificial intelligence, uses evolution creating neural networks, parameters, topology, and rules. Evolution apply mutation, recombination, selection mechanisms finding networks with behavior that satisfies to conditions some formally defined problem. In this paper, we demonstrate use programs problems. Hyperscheme high-level parameterized specification solving class Setting values hyperscheme parameters further interpretation allows obtaining adapted specific their use. Automated construction based them implemented integrated toolkit design synthesis programs. Glushkov systems algorithmic algebra. schemes built using dialogue constructor syntactically correct programs, consists descending by detailing constructions language. represented as tree. Based schemes, target language generated. results experiment consisting executing generated evaluating program cloud platform given.