Innovative opportunities of scientific software and integration components of virtual semantic environment for autonovous systems

Abstract

The initial stage of concept implementation of control the development of hybrid systems is presented. The aspect of anticipating new opportunities for the active self-developing reflexive environment is shown. Bioinspired models relationship management of pertinent information streams for development a virtual semantic environment and methods of these models integration are presented. In this paper, the problem-based learning systems and integration of its intellectual components into expert systems are investigated using data envelopment analysis approach. Accelerated staff training is a factor of future effectiveness of mixed groups of robotic systems created from these basic components. Also, effectiveness achieved by taking into account the information on the latest developments, and using the high-quality software and training facilities on the test bench, i.e. by improving training and material support of universities. An implementation of the original problem-oriented system on the basis of pertinent search algorithms for processing of information resources is invited to consider for further comprehensive study of the conditions and interaction information. Simulation the activity of mixed robotic groups is performed by using the knowledge base on bionic technology. The innovative potential of the virtual environment in the long term can be used for development an unmanned vehicle as a component of intelligent city. Another application of the proposed approach is 3D-visualization software and hardware solutions and integration of its components in the simulation of mixed (including multi-media) robotics groups and even game applications. At present, computational neuroscience as the basis for such an interdisciplinary field of research on intellectual (affective) computing is rapidly evolving. It is an interdisciplinary computational science that links the diverse fields of neuroscience, cognitive science, and psychology with electrical engineering, computer science, mathematics, and physics. It studies brain function in terms of the information processing properties of the structures that make up the nervous system. The ideas of Radchenko are developed by the modern modeling tools in this paper. The basic components of ambient intelligence are presented.