Training in STEM centers is becoming increasingly relevant in order to meet the new educational needs caused mainly by the rapid speed with which new technologies have been entering our lives in recent years. Existing university e-learning systems can enhance the capacity of these centers by providing shared learning material. This paper presents a distributed educational platform that supports sharable usage of teaching material at university and in STEM centers in secondary schools. The architecture of the platform is also presented including two basic components. The university e-learning environment operates as a back-end and the front-end component is located in the STEM center. Furthermore, the implemented prototype of the platform is also discussed in the article. The use of the platform is demonstrated by two educational games. The platform is expanded with four educational robots to increase the attractiveness of the educational process.

Portfolio management is a process involving decision making in dynamic and unpredictable environment. Asset allocation plays a key role in this process, since the optimal use of the capital is a complex and resource-consuming problem. During our research in this field we have detected some problems that lead to biased results and one of them occurs in case of limited financial resources. In this paper a mathematical assessment of the dependence of the capital, used on asset prices is derived, and a multi-step procedure for asset allocation, aiming at optimization of the investor’s utility in case of limited resources is described. The procedure is implemented as a module in a decision support system based on fuzzy logic. The paper contains comparison of the obtained test results with results from the classical Markowitz portfolio model. The conducted tests are on real data from the Bulgarian stock exchange.

This paper presents an environment which generates tests automatically. It is designed for assistance in the software engineering education and is part of the Virtual Education Space. The environment has two functionalities – generation and assessment of different types of test questions. In the paper, the architecture of the environment is described in detail. The test generation is supported by specialized ontologies, which are served by two intelligent agents known as Questioner Operative and Assessment Operative.

The e-learning environment known as VES (the Virtual Education Space) was created at the University of Plovdiv “Paisii Hilendarski” in Bulgaria step by step for years as each subsequent version was built on the previous one. Initially a learning system called DeLC (the Distributed e-Learning Center) has been implemented to support blended and independent learning at the Faculty of Mathematics and Informatics at the university. DeLC was a successful project, but we identified some problems, connected with interactions between the virtual and the physical world where in fact the learning process takes place. In the following period, we started the development of ViPS (the Virtual Physical Space) based on concepts of CPSS (Cyber-Physical-Social System) and IoT (Internet of Things). VES is the ViPS adaptation to education. VES is the successor to DeLC, it provides e-learning content and e-learning education services for planning, organizing, and conducting the learning process at the Faculty of Mathematics and Informatics of the University of Plovdiv.VES supports various forms of e-learning such as blended learning, self-paced learning, lifelong learning, inclusive and game-based learning (GBL). The following aspects of VES are essential: 1) users are the focus of attention; 2) physical “things” are virtualized; 3) there is integration between the virtual and the physical worlds. Since ViPS is developed as a CPSS ecosystem, users are the focus of attention. This determines the need to develop personal assistants to participate in the processes of the ViPS space on behalf of and in the interest of users. Three intelligent agents are modeled in VES: an internal educational agent, an external educational agent, and a career consultant. MATE (the Multi-Agent Testing Environment) is a component supported in the ViPS space for training and testing of students in a game-based manner. MATE is a set of autonomous agents, each one of which has responsibilities in the common architecture that arise from training and testing needs.As a CPSS space, VES introduces new approaches and scenarios to solve complex problems in the field of e-learning. VES provides a reference architecture, which can be adapted for various forms of education supported by information and communication technologies.

Plovdiv faces significant air pollution challenges due to geographic, climatic, and industrial factors, making accurate air quality assessment critical. This study presents a hybrid multi-agent platform that integrates symbolic and sub-symbolic artificial intelligence to improve the reliability of air quality monitoring. The platform features a BDI agent, developed using JaCaMo, for processing real-time sensor measurements and a ReAct agent, implemented with LangChain, to incorporate external data sources and perform advanced analytics. By combining these AI approaches, the platform enhances data integration, detects anomalies, and resolves discrepancies between conflicting air quality reports. Furthermore, its scalable and adaptable architecture lays the foundation for future advancements in environmental monitoring. This research represents the first stage in developing an AI-powered system that supports more objective and data-driven decision-making for air quality management in Plovdiv.

This paper describes a model of modular system for Rapid Application Development of Web-based Information Systems (RADWIS). The existing modular systems on technology, framework and platform level does not fully solve the problems of functionality reuse, rapid application development and balance between the complexity, size and functionality. The proposed modular system addresses these problems in a new way. The current work fills the gap between the modular systems on the framework and platform level. The model uses flexible, reusable modules, which can be built with different technologies. They are installable and shareable with the standard dependency manager of the technology and can communicate using web services. The modules use NoSQL approaches in SQL databases. A workflow engine module, based on the Petri Nets theory, allows a graphical and formal mathematical solution for a wide variety of problems.