The problem of wireless sensor-actuator network design as a part of the mobile cyber-physical system is considered. The ways of implementation of the wireless connections scheme are analyzed. The network structure and algorithms of its operation are proposed. The design of the sensor and actuator nodes based on the wireless SoC ESP8266 is presented.

The problem of context-aware task sequence planning by an autonomous intelligent system (intelligent agent) for a case of independent or loosely coupled tasks is considered. The principle of matching the task to the context was analyzed, the structure of the task sequence planning module and the algorithm of its work were proposed. The paper also proposes an algorithm for calculating the dynamic priority of a task, an algorithm for determining whether a task meets context, and an algorithm for adapting a set of rules for matching tasks to a context based on reinforcement learning in a stationary random environment with context dependence (contextual multi-armed bandit problem). The outline of the reinforcement learning procedure, implemented in the prototype of the task sequence planning module, has been proposed.

The problem of designing a master of computer engineering program with a specialization in cyber-physical systems has been considered. The concept of cyber-physical systems has been analyzed from the perspective of generalization and formalization for educational purposes. The need for designing a master program in cyber-physical systems has been justified. Program competencies and learning outcomes have been defined. The structure of the master of computer engineering program with a specialization in cyber-physical systems and the corresponding structural-logical scheme of master's training have been regarded.

The paper considers the problem of distributed adaptation of the functional integration structure of a multi-agent system in a dual-tasking environment from the point of view of organizing multi-agent search and use of the functional emergence effect provided by different structures of functional integration. The considered problem belongs to a wider class of problems of structural adaptation and self-organization. Models of functional integration, in particular, models based on general quantitative characteristics of the functional roles distribution of agents and models based on local qualitative characteristics of the functional roles distribution of agents, taking into account the specifics of functional links established between agents have been considered in the paper. The problems of the distributed adaptation of the functional integration structure have been analyzed, including the problem of the functional specialization of agents in a multitasking environment. Various ways of organizing structural changes have been considered, including multi-agent parametric adaptation based on a local structural parameter. Multi-agent structural adaptation based on reinforcement learning methods, in particular, multi-agent structural adaptation based on the normalized exponential function method (MSA-softmax) and multi-agent structural adaptation based on the upper confidence bound method (MSA-UCB) has been proposed. The distributed adaptation methods simulation results have been presented, which showed the advantage of multi-agent structural adaptation over multi-agent parametric adaptation.

The problem of context-aware task sequence planning by an autonomous intelligent system (intelligent agent) for a case of independent or loosely coupled tasks is considered. The principle of matching the task to the context was analyzed, the structure of the task sequence planning module and the algorithm of its work were proposed. The paper also proposes an algorithm for calculating the dynamic priority of a task, an algorithm for determining whether a task meets context, and an algorithm for adapting a set of rules for matching tasks to a context based on reinforcement learning in a stationary random environment with context dependence (contextual multi-armed bandit problem). The outline of the reinforcement learning procedure, implemented in the prototype of the task sequence planning module, has been proposed.

The problem of designing a master of computer engineering program with a specialization in cyber-physical systems has been considered. The concept of cyber-physical systems has been analyzed from the perspective of generalization and formalization for educational purposes. The need for designing a master program in cyber-physical systems has been justified. Program competencies and learning outcomes have been defined. The structure of the master of computer engineering program with a specialization in cyber-physical systems and the corresponding structural-logical scheme of master's training have been regarded.

The paper considers the problem of distributed adaptation of the functional integration structure of a multi-agent system in a dual-tasking environment from the point of view of organizing multi-agent search and use of the functional emergence effect provided by different structures of functional integration. The considered problem belongs to a wider class of problems of structural adaptation and self-organization. Models of functional integration, in particular, models based on general quantitative characteristics of the functional roles distribution of agents and models based on local qualitative characteristics of the functional roles distribution of agents, taking into account the specifics of functional links established between agents have been considered in the paper. The problems of the distributed adaptation of the functional integration structure have been analyzed, including the problem of the functional specialization of agents in a multitasking environment. Various ways of organizing structural changes have been considered, including multi-agent parametric adaptation based on a local structural parameter. Multi-agent structural adaptation based on reinforcement learning methods, in particular, multi-agent structural adaptation based on the normalized exponential function method (MSA-softmax) and multi-agent structural adaptation based on the upper confidence bound method (MSA-UCB) has been proposed. The distributed adaptation methods simulation results have been presented, which showed the advantage of multi-agent structural adaptation over multi-agent parametric adaptation.

Abstract: The model of decentralized control of adaptive data collection processes has been developed based on the equilibrium concept, which is used to study the problem of coordinating joint collective actions from the point of view of finding an effective scheme for complementing the individual actions of data collection processes in the absence of a control center. The method of decentralized control of adaptive data collection processes in autonomous distributed systems based on the equilibrium concept and reinforcement learning by the method of normalized exponential function (softmax) has been developed. The method allows one to organize autonomous distributed exploration under the conditions of dynamic changes in the number of data collection processes and unreliable local information interaction between them. As a result of research and modeling of the developed method of decentralized control, it has been established that the use of the reinforcement learning (normalized exponential function method) provides more effective search for a solution compared to the method of adaptive random search (by an average of 28,3 %). Using the efficiency retention rate, an estimate was obtained for the dependence of the work of the developed decentralized control method on the change in the number of adaptive data collection processes and the change in the information interaction channels between adaptive data collection processes.

Abstract - The problem of developing an online video platform with a context-aware content-based recommender system has been considered. Approaches to developing online video platforms have been considered. A comparison of popular online video platforms has been presented. A method of context-aware content-based recommendation of videos has been proposed. A method involves saving information about user interaction with video, obtaining and storing information about which videos the user liked, determining user context, composing a profile of user preferences, composing a profile of user preferences depending on context, determining the similarity between the video profile and a profile of user preferences (with and without context consideration), determining the relevance of the video to the context, the conclusive estimation of the relevance of the video to the user's preferences based on the proposed composite relevance indicator. The developed structure of online video platform has been presented. The algorithm of its work has been considered. The structure of the online video platform database has been proposed. Features of designing the user interface of the online video platform have been considered. The issue of testing the developed online video platform has been considered.

Abstract - The problem of developing a software service with a plug-in architecture for assessing the readability of text has been considered. The problem of text readability assessment has been analyzed. Approaches to the development of a software service for text readability assessment have been considered. The structure of the service for text readability assessment has been proposed. The structure of the service has been implemented using the Python programming language and the library Natural Language Toolkit. The results of testing the service for text readability assessment have been presented.