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  • Управление процессами морской логистики в нефтяной отрасли: анализ и совершенствование с помощью агентно-ориентированных имитационных моделей
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News
July 20, 2026
Scientists Create Open Dataset for Studying Concentration
A team of Russian researchers, including scientists from HSE University–St Petersburg, has developed the first open multimodal dataset containing recordings of brain activity, heart function, and video observations to help researchers understand what happens in the human brain during deep concentration. In the future, the dataset could accelerate the development of neural interfaces, rehabilitation technologies, and AI systems. The article has been published in Scientific Data.
July 20, 2026
‘Science Is Universal-It Knows No Borders
Fuad Aleskerov, Tenured Professor and Director of the International Centre of Decision Choice and Analysis at HSE University, together with his colleagues, has developed methods of network analysis in bibliometrics that have made it possible to identify patterns in the appearance and citation of publications in academic journals, as well as their influence on each other. When one or a number of studies are frequently cited by a wide range of journals, this is an indicator that the research is of high quality. By contrast, extensive cross-citation within a limited group of journals increases the likelihood of identifying a network of predatory publications.
July 20, 2026
Scientists Propose Method for More Efficient Resource Use in Machine Learning
An international group of researchers, including mathematicians from the AI and Digital Science Institute at the HSE Faculty of Computer Science, has provided a theoretical justification for a simple and computationally efficient method of estimating uncertainty in Stochastic Gradient Descent (SGD). The paper has been published on the scientific preprint server arXiv.org and presented at AISTATS 2026.

 

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Управление процессами морской логистики в нефтяной отрасли: анализ и совершенствование с помощью агентно-ориентированных имитационных моделей

Судостроение. 2024. № 1(872). С. 61–68.
Serova E., Шкляев Д. О., Сумятина В. О.

Intelligent business transformation — one of the main directions of qualitative development within modern economy. The analysis of the problems associated with the progressing of the theory and practice of maritime logistics in the oil industry, especially in the last decade, is carried out taking into account the application of a systems approach and modern intelligent systems, distributed artificial intelligence systems. As a result of the 4th industrial revolution technologies integration into the oil industry, such as artificial intelligence (AI), 5G, cloud computing, IoT, and the constant development of the eco-system of AI applications, it is going the evolving of the industry and expanding business opportunities for innovation. Resources such as oil and gas are associated with government regulation and life support of the population, so all the supply chain links must meet the requirements of effective management and ensuring a high level of competitiveness. Artificial intelligence is an important strategic technology that allows the oil industry to respond promptly to ongoing changes in logistics flows and efficiently manage them. One of the most effective ways to solve managerial problems of multifunctional logistics is application of methods and systems of modeling, first of all, multi-agent systems (MAS), belonging to the class of distributed artificial intelligence systems. Despite the abundance of researches on the theory and methodology application of different modeling approaches and systems in maritime logistics, the most effective and correct ways of their application are constantly being searched. The article is devoted to the consideration of issues related to the application of simulation in maritime logistics in the oil industry, in particular, agent-based modeling.

Research target: Computer Science Mathematics Economics and Management
Language: Russian
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Keywords: агентное моделированиесистемы распределенного искусственного интеллектацифровые двойникиdigital twinsdistributed artificial intelligence systems agent-based modelingmanagement of maritime logistics processes in the oil industryуправление процессами морской логистики в нефтяной отрасли
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