Применение генетических алгоритмов при разработке адаптивных алгоритмов передвижения робота
In this work, in order of development of the previously proposed decision support system to counteract the development of infectious diseases (DSS «CDID») it is proposed evolutionary model (EM), that extends the capabilities of forecast – analytical studies on the spread of infectious disease processes for individual cities and areas of the country as a whole, as well as early assessment of ways solutions to the problems of prophylaxis and therapy in the study territories.
Article is devoted to the analysis of the main directions of development of an educational robotics, mechatronics and scientific and technical creativity of youth in the Russian Federation. The author gives the analysis of the modern market of educational designers and sets of a robotics, makes practical recommendations of use of training models in educational process.
The companies that are IT-industry leaders perform from several tens to several hundreds of projects simultaneously. The main problem is to decide whether the project is acceptable to the current strategic goals and resource limits of a company or not. This leads firms to an issue of a project portfolio formation; therefore, the challenge is to choose the subset of all projects which satisfy the strategic objectives of a company in the best way. In this present article we propose the multi-objective mathematical model of the project portfolio formation problem, defined on the fuzzy trapezoidal numbers. We provide an overview of methods for solving this problem, which are a branch and bound approach, an adaptive parameter variation scheme based on the epsilon-constraint method, ant colony optimization method and genetic algorithm. After analysis, we choose ant colony optimization method and SPEA II method, which is a modification of a genetic algorithm. We describe the implementation of these methods applied to the project portfolio formation problem. The ant colony optimization is based on the max min ant system with one pheromone structure and one ant colony. Three modification of our SPEA II implementation were considered. The first adaptation uses the binary tournament selection, while the second requires the rank selection method. The last one is based on another variant of generating initial population. The part of the population is generated by a non-random manner on the basis of solving a one-criterion optimization problem. This fact makes the population more strongly than an initial population, which is generated completely by random. Comparing of ant colony optimization algorithm and three modifications of a genetic algorithm was performed. We use the following parameters: speed of execution and the C-metric between each pair of algorithms. Genetic algorithm with non-random initial population show better results than other methods. Thus, we propose using this algorithm for solving project portfolio formation problem.
In the present paper, on the basis of the theory of production principles and production revolutions, we reveal the interrelation between K-waves and major technological breakthroughs in history and make forecasts about features of the sixth Kondratieff wave in the light of the Cybernetic Revolution that, from our point of view, started in the 1950s. We assume that the sixth K-wave in the 2030s and 2040s will merge with the final phase of the Cybernetic Revolution (which we call a phase of self-regulating systems). This period will be characterized by the breakthrough in medical technologies which will be capable to combine many other technologies into a single complex of MBNRIC-technologies (med-bio-nano-robo-info-cognitive technologies). The article offers some forecasts concerning the development of these technologies.
Relations between the human and hi-tech worlds, even until recently considered the subject of science fiction, are taking a more real shape and becoming the focus of expert discussions. Some specialists suggest that in the future machines can become the principal creator of new technologies and race far ahead of humanity. However, emerging technologies for human enhancement offer new possibilities for humans to remain competitive against machines and to acquire more advanced physical and mental capacities. These techniques are interdisciplinary, drawing primarily on advances in medicine, pharmacology, nutrition, mobile communications, neuroscience and cognitive sciences. This paper provides examples of such developments, analyzes their contribution to the expansion of human capabilities and, consequently, implications for the future working environment. It addresses ethical issues and risks associated with human enhancement technologies, in particular, the emergence of the new social divide - between the users of such technologies and people lacking access to them. Finally, it discusses some wild cards that may cause future surprises and shocks, i.e. machines that can control a human-excluded world, a virtual level of human life that dominates real life. The author notes that such conditions will require rethinking established views of personality, human responsibility and mutual obligations that will help the establishment of new behavioral patterns.