This study introduces a multi-agent reinforcement learning approach to address the challenges of real-time scheduling in dynamic environments, with a specific focus on healthcare operations. The proposed system integrates the Human-in-the-Loop (HITL) paradigm, providing continuous feedback from human evaluators, and it employs a sophisticated reward function to attenuate the effects of human-driven events. Novel mapping between reinforcement learning (RL) concepts and the Belief–Desire–Intention (BDI) framework is developed to enhance the explainability of the agent’s decision-making. A system is designed to adapt to changes in patient conditions and preferences while minimizing disruptions to existing schedules. Experimental results show a notable decrease in patient waiting times compared to conventional methods while adhering to operator-induced constraints. This approach offers a robust, explainable, and adaptable solution for the challenging tasks of scheduling in the environments that require human-centered decision-making.

Development of the web portal for research support in the area of electrical impedance tomography

The article considers the structures of representation of the graph of inter-agent connections for increasing the efficiency of agent interaction in cooperative competitive games using graph neural networks. A comparative assessment of metrics and adjacency matrices for graphs of connections defined using geometric and semantic metrics of proximity is performed. It is shown that semantic proximity is more effective in constructing a graph of inter-agent connections, and the use of oriented graphs ensures flexible management of information flows. The proposed patterns are important to consider when organizing multi-agent reinforcement learning in a wide range of application areas.

The creation of native information systems for mobile devices in healthcare facilities is becoming increasingly important in light of the need for remote monitoring of patients» condition. This need is due to the necessity for medical staff to constantly monitor patient condition in order to make quick decisions in the case of an emergency. In this regard the article is devoted to the technical aspects of developing a mobile application for remote interaction with an electrical impedance tomography device. Unlike well-known solutions, which use Bluetooth technology for information transfer, this article focuses on the study of the features of working with ­TCP sockets, which are an integral part of data transfer between the electrical impedance tomography machine and a mobile device. Also, the use of ­TCP sockets is due to the existing implementation of this technology in an electrical impedance tomography device made for its integration with a lung ventilator. The article discusses the main aspects of developing a system for remote interaction with medical equipment using the example of an electrical impedance tomography device. An application prototype developed for the i­OS operating system to test the applicability of the proposed approach is described. The authors of the article describe methods for receiving graphic data, and also discuss possible problems and solutions related to working with ­TCP sockets in a mobile application.