The article substantiates the possibilities of implementing network programs of higher and additional professional education based on multi-agent technologies that transform all basic educational processes, ensuring their flexibility and adaptability to the dynamic needs of the labor market. The use of multi-agent technologies for engineering education, which is characterized by the use of complex and high-cost software, hardware and engineering systems that require the organization of collective sharing of resources, is becoming especially relevant. For multi-agent technologies, a method is chosen for representing agents in the form of asset administrative shells of fourth-generation industry systems, representing digital twins of information, educational, software, technical and organizational-methodological resources. The article proposes the structure of a multi-agent networked learning system; requirements for information representation of educational processes and the composition of key services in the asset administrative shells are defined. It introduces a multi-agent technology for the interaction of participants in the creation of networked educational programs. The software implementation of a multi-agent networked learning system based on the FIPA (Foundation for Intelligent Physical Agents) standards and the specifications of the asset administrative shells of the Platform Industry 4.0 project will enhance the adaptability of networked educational programs. This will be achieved through the individualization of the learning process, with the real-time involvement of resources from various educational institutions and the collective use of software, technical, and engineering complexes. The collection of big data on the execution of educational processes in the asset administrative shells will contribute to both the real-time adjustment of the multi-agent system to the evolving competency model of learners and the improvement of the educational content throughout the entire system. The research results presented in the article will be applicable in teaching the courses "Design of Intelligent Information Systems" (bachelor's degree) and "Knowledge Engineering" (master's degree) in the field of study "Applied Informatics."
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Telnov et al. (2024) studied this question.
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