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In this paper, we propose an adaptive algorithm that simulates the process of forming the initial behavioral skills on the example of the system ‘eye-arm’ animat. The situation is the formation of the initial behavioral skills occurs, for example, when a child masters the management of their hands by understanding the relationship between baseline unidentified spots on the retina of his eye and the position of the real object. Since the body control skills are not ‘hardcoded’ initially in the brain and the spinal cord at the level of instincts, the human child, like most young of other mammals, it is necessary to develop these skills in search behavior mode. Exploratory behavior begins with trial and error and then its contribution is gradually reduced as the development of the body and its environment. Since the correct behavior patterns at this stage of development of the organism does not exist for now, then the only way to select the right skills is a positive reinforcement to achieve the objective. A key feature of the proposed algorithm is to fix in the imprinting mode, only the final action that led to success, and that is very important, led to the familiar imprinted situation clearly leads to success. Over time, the continuous chain is lengthened right action — maximum use of previous positive experiences and negative ‘forgotten’ and not used.

Thus there is the gradual replacement of the random search purposeful actions that observed in the real young. Thus, the algorithm is able to establish a correspondence between the laws of the world and the ‘inner feelings’, the internal state of the animat. The proposed animat model was used 2 types of neural networks: 1) neural network NET1 to the input current which is fed to the position of the brush arms and the target point, and the output of motor commands, directing ‘brush’ manipulator animat to the target point; 2) neural network NET2 is received at the input of target coordinates and the current coordinates of the ‘brush’ and the output value is formed likelihood that the animat already ‘know’ this situation, and he ‘knows’ how to react to it. With this architecture at the animat has to rely on the ‘experience’ of neural networks to recognize situations where the response from NET2 network of close to 1, and on the other hand, run a random search, when the experience of functioning in this area of the visual field in animat not (response NET2 close to 0).

We describe an engineering-psychological experiment that continues the study of ways to adapt a person to the increasing complexity of logical problems by presenting a series of problems of increasing complexity, which is determined by the volume of initial data. Tasks require calculations in an associative or non-associative system of operations. By the nature of the change in the time of solving the problem, depending on the number of necessary operations, we can conclude that a purely sequential method of solving problems or connecting additional brain resources to the solution in parallel mode. In a previously published experimental work, a person in the process of solving an associative problem recognized color images with meaningful images. In the new study, a similar problem is solved for abstract monochrome geometric shapes. Analysis of the result showed that for the second case, the probability of the subject switching to a parallel method of processing visual information is significantly reduced. The research method is based on presenting a person with two types of tasks. One type of problem contains associative calculations and allows a parallel solution algorithm. Another type of problem is the control one, which contains problems in which calculations are not associative and parallel algorithms are ineffective. The task of recognizing and searching for a given object is associative. A parallel strategy significantly speeds up the solution with relatively small additional resources. As a control series of problems (to separate parallel work from the acceleration of a sequential algorithm), we use, as in the previous experiment, a non-associative comparison problem in cyclic arithmetic, presented in the visual form of the game “rock, paper, scissors”. In this problem, the parallel algorithm requires a large number of processors with a small efficiency coefficient. Therefore, the transition of a person to a parallel algorithm for solving this problem is almost impossible, and the acceleration of processing input information is possible only by increasing the speed. Comparing the dependence of the solution time on the volume of source data for two types of problems allows us to identify four types of strategies for adapting to the increasing complexity of the problem: uniform sequential, accelerated sequential, parallel computing (where possible), or undefined (for this method) strategy. The Reducing of the number of subjects, who switch to a parallel strategy when encoding input information with formal images, shows the effectiveness of codes that cause subject associations. They increase the speed of human perception and processing of information. The article contains a preliminary mathematical model that explains this phenomenon. It is based on the appearance of a second set of initial data, which occurs in a person as a result of recognizing the depicted objects.

Database to store, search and retrieve DNA physical properties profiles has been developed and its use for analysis of E. coli promoters has been demonstrated. Unique feature of the database is in its ability to handle whole profile as single internal object type in a way similar to integers or character strings. To demonstrate utility of such database it was populated with data of 1227 known promoters, their nucleotide sequence, profile of electrostatic potential, transcription factor binding sites. Each promoter is also connected to all genes, whose transcription is controlled by that promoter. Content of the database is available for search via web interface. Source code of profile datatype and library to work with it from R/Bioconductor are available from the internet, dump of the database is available from authors by request.

A dynamic game theoretic model of struggle against corruption in resource allocation is considered. It is supposed that the system of resource allocation includes one principal, one or several supervisors, and several agents. The relations between them are hierarchical: the principal influences to the supervisors, and they in turn exert influence on the agents. It is assumed that the supervisor can be corrupted. The agents propose bribes to the supervisor who in exchange allocates additional resources to them. It is also supposed that the principal is not corrupted and does not have her own purposes. The model is investigated from the point of view of the supervisor and the agents. From the point of view of agents a non-cooperative game arises with a set of Nash equilibria as a solution. The set is found analytically on the base of Pontryagin maximum principle for the specific class of model functions. From the point of view of the supervisor a hierarchical Germeyer game of the type Г_2t is built, and the respective algorithm of its solution is proposed. The punishment strategy is found analytically, and the reward strategy is built numerically on the base of a discrete analogue of the initial continuous- time model. It is supposed that all agents can change their strategies in the same time instants only a finite number of times. Thus, the supervisor can maximize his objective function of many variables instead of maximization of the objective functional. A method of qualitatively representative scenarios is used for the solution. The idea of this method consists in that it is possible to choose a very small number of scenarios among all potential ones that represent all qualitatively different trajectories of the system dynamics. These scenarios differ in principle while all other scenarios yield no essentially new results. Then a complete enumeration of the qualitatively representative scenarios becomes possible. After that, the supervisor reports to the agents the rewardpunishment control mechanism.

A critical analysis of existing approaches, methods and models to solve the problem of financial resources operational management has been carried out in the article. A number of significant shortcomings of the presented models were identified, limiting the scope of their effective usage. There are a static nature of the models, probabilistic nature of financial flows are not taken into account, daily amounts of receivables and payables that significantly affect the solvency and liquidity of the company are not identified. This necessitates the development of a new model that reflects the essential properties of the planning financial flows system — stochasticity, dynamism, non-stationarity.

The model for the financial flows distribution has been developed. It bases on the principles of optimal dynamic control and provides financial resources planning ensuring an adequate level of liquidity and solvency of a company and concern initial data uncertainty. The algorithm for designing the objective cash balance, based on principles of a companies’ financial stability ensuring under changing financial constraints, is proposed.

Characteristic of the proposed model is the presentation of the cash distribution process in the form of a discrete dynamic process, for which a plan for financial resources allocation is determined, ensuring the extremum of an optimality criterion. Designing of such plan is based on the coordination of payments (cash expenses) with the cash receipts. This approach allows to synthesize different plans that differ in combinations of financial outflows, and then to select the best one according to a given criterion. The minimum total costs associated with the payment of fines for non-timely financing of expenses were taken as the optimality criterion. Restrictions in the model are the requirement to ensure the minimum allowable cash balances for the subperiods of the planning period, as well as the obligation to make payments during the planning period, taking into account the maturity of these payments. The suggested model with a high degree of efficiency allows to solve the problem of financial resources distribution under uncertainty over time and receipts, coordination of funds inflows and outflows. The practical significance of the research is in developed model application, allowing to improve the financial planning quality, to increase the management efficiency and operational efficiency of a company.

This article is devoted to the development of an algorithm for trajectory control of a highly maneuverable four-wheeled robotic transport platform equipped with mecanum wheels, in order to organize its movement behind some moving object. The calculation of the kinematic ratios of this platform in a fixed coordinate system is presented, which is necessary to determine the angular velocities of the robot wheels depending on a given velocity vector. An algorithm has been developed for the robot to follow a mobile object on a plane without obstacles based on the use of a modified chase method using different types of control functions. The chase method consists in the fact that the velocity vector of the geometric center of the platform is co-directed with the vector connecting the geometric center of the platform and the moving object. Two types of control functions are implemented: piecewise and constant. The piecewise function means control with switching modes depending on the distance from the robot to the target. The main feature of the piecewise function is a smooth change in the robot’s speed. Also, the control functions are divided according to the nature of behavior when the robot approaches the target. When using one of the piecewise functions, the robot’s movement slows down when a certain distance between the robot and the target is reached and stops completely at a critical distance. Another type of behavior when approaching the target is to change the direction of the velocity vector to the opposite, if the distance between the platform and the object is the minimum allowable, which avoids collisions when the target moves in the direction of the robot. This type of behavior when approaching the goal is implemented for a piecewise and constant function. Numerical simulation of the robot control algorithm for various control functions in the task of chasing a target, where the target moves in a circle, is performed. The pseudocode of the control algorithm and control functions is presented. Graphs of the robot’s trajectory when moving behind the target, speed changes, changes in the angular velocities of the wheels from time to time for various control functions are shown.

Industrial robots have made it possible for robotics to become a worldwide discipline both in economy and in science. However, their capabilities are limited, especially regarding contact tasks where it is required to regulate or at least limit contact forces. At one point, it was noticed that elasticity in the joint transmission, which was treated as a drawback previously, is actually helpful in this regard. This observation led to the introduction of elastic joint robots that are well-suited to contact tasks and cooperative behavior in particular, so they become more and more widespread nowadays. Many researchers try to implement such devices not with trivial series elastic actuators (SEA) but with more sophisticated variable stiffness actuators (VSA) that can regulate their own mechanical stiffness. All elastic actuators demonstrate shock robustness and safe interaction with external objects to some extent, but when stiffness may be varied, it provides additional benefits, e. g., in terms of energy efficiency and task adaptability. Here, we present a novel variable stiffness actuator with a magnetic coupler as an elastic element. Magnetic transmission is contactless and thus advantageous in terms of robustness to misalignment. In addition, the friction model of the transmission becomes less complex. It also has milder stiffness characteristic than typical mechanical nonlinear springs, moreover, the stiffness curve has a maximum after which it descends. Therefore, when this maximum torque is achieved, the coupler slips, and a new pair of poles defines the equilibrium position. As a result, the risk of damage is smaller for this design solution. The design of the joint is thoroughly described, along with its mathematical model. Finally, the control system is also proposed, and simulation tests confirm the design ideas.

Now days the main research activity in the field of nanotechnology is aimed at the creation, study and application of new materials and new structures. Recently, much attention has been attracted by the possibility of controlling magnetic properties using a superconducting current, as well as the influence of magnetic dynamics on the current–voltage characteristics of hybrid superconductor/ferromagnet (S/F) nanostructures. In particular, such structures include the S/F/S Josephson junction or molecular nanomagnets coupled to the Josephson junctions. Theoretical studies of the dynamics of such structures need processes of a large number of coupled nonlinear equations. Numerical modeling of hybrid superconductor/magnet nanostructures implies the calculation of both magnetic dynamics and the dynamics of the superconducting phase, which strongly increases their complexity and scale, so it is advisable to use heterogeneous computing systems.

In the course of studying the physical properties of these objects, it becomes necessary to numerically solve complex systems of nonlinear differential equations, which requires significant time and computational resources.

The currently existing micromagnetic algorithms and frameworks are based on the finite difference or finite element method and are extremely useful for modeling the dynamics of magnetization on a wide time scale. However, the functionality of existing packages does not allow to fully implement the desired computation scheme.

The aim of the research is to develop a unified environment for modeling hybrid superconductor/magnet nanostructures, providing access to solvers and developed algorithms, and based on a heterogeneous computing paradigm that allows research of superconducting elements in nanoscale structures with magnets and hybrid quantum materials. In this paper, we investigate resonant phenomena in the nanomagnet system associated with the Josephson junction. Such a system has rich resonant physics. To study the possibility of magnetic reversal depending on the model parameters, it is necessary to solve numerically the Cauchy problem for a system of nonlinear equations. For numerical simulation of hybrid superconductor/magnet nanostructures, a computing environment based on the heterogeneous HybriLIT computing platform is implemented. During the calculations, all the calculation times obtained were averaged over three launches. The results obtained here are of great practical importance and provide the necessary information for evaluating the physical parameters in superconductor/magnet hybrid nanostructures.