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November 10, 2026
Physicists Train AI to Optimise Particle Beams in Accelerators
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science and the Budker Institute of Nuclear Physics at the Siberian Branch of the Russian Academy of Sciences have developed RLABC (Reinforcement Learning for Accelerator Beamline Control), a framework that uses reinforcement learning to identify optimal settings for a particle accelerator. In a computer simulation, RLABC optimised the accelerator's parameters to achieve a particle transmission rate of 70%. The study has been published in Computer Physics Communications.
November 9, 2026
'Organ-on-a-Chip Technology Could Eliminate the Need for Animal Testing'
The Laboratory of Molecular Physiology at the HSE Faculty of Biology and Biotechnology investigates how molecular regulators known as microRNAs control gene expression and contribute to the development of diseases, including cancer, viral and inflammatory conditions, and pregnancy complications. At HSE University, researchers develop organ-on-a-chip models: miniature devices containing living cells that mimic the functions of human organs, such as the placenta and intestines. These models help researchers understand how diseases develop and how drugs affect them. HSE News Service spoke with Evgeny Knyazev, Head of the Laboratory.
November 9, 2026
Flattened Terrain Models Underestimate Vehicle-to-Vehicle Communication Outages
Researchers at HSE MIEM have shown that widely used simulators of vehicle-to-vehicle communication significantly overestimate its reliability because they assume flat terrain. When terrain features, bridges, and tunnels are taken into account, the outage rate on a mountain serpentine road rises from 21% to 30%, on an overpass from 20% to 33%, and in a tunnel from 0% to 80%. The results have been published in Future Transportation.

 

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Infinite Horizon Dynamic Games: A New Approach via Information Updating

International Game Theory Review. 2017. Vol. 19. No. 4. P. 1–23.
Petrosian O., Yeung D.

We introduce a new sequential game, where each player has a limited resource that he needs to spend on increasing the probability of winning each stage, but also on maintaining the assets that he has won in the previous stages. Thus, the players’ strategies must take into account that winning at any given stage negatively affects the chances of winning in later stages. Whenever the initial resources of the players are not too small, we present explicit strategies for the players, and show that they are a Nash equilibrium, which is unique in an appropriate sense.

Priority areas: economics IT and mathematics mathematics
Language: English
Full text
DOI
Keywords: dynamic gameslooking forward approachinfinite game horizoninformation updatinguncertain payoff structures
Publication based on the results of:
­­­Axiomatic aspects of fair division problems (2017)
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