Cluster analysis of a collective of algorithms for multicore neural network automates and robots on chip

Machine learning and knowledge control systems
Authors:
Abstract:

Within the framework of increasing the efficiency of new spheres and directions of development of society, the state pays attention to robotization on a modern domestic basis in order to implement import substitution. One of the urgent problems is the combination of the concepts of a collective of algorithms, a collective of automata, a collective of robots and artificial intelligence. A special role is played by the possibilities of cybernetic research of multicore neural network automata in order to build more complex automata, robots and the behavior of a team of robots based on them. The purpose of this article is to demonstrate the possibilities of a set-theoretic approach of a cybernetic approach to artificial, complex natural objects and systems on this basis and to create a conceptual model for the selection and joint simultaneous design of hardware and software of neural network automata based on a unified study of the processes of parallelization of a collective of algorithms in the form of explicit and implicit clustering. As a result, the authors analyze, show and propose variants of the collective structures of algorithms for ensuring cybersecurity and protection against threats in the form of a hierarchy of security practices. The method of analysis and selection of the best architecture of a multicore neural network collective of an automaton and a robot collective based on automata implemented on a chip is proposed. An expert system based on VLSI 1879VM8YA (NM6408) with a developed user interface is being implemented.