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Ukraine: Russland intensiviert vor Lieferung von F-16-Kampfflugzeugen Angriffe
Russland intensiviert nach Einschätzung der Ukraine angesichts angekündigter Lieferungen von Kampfflugzeugen und weiteren westlichen Militärhilfen für Kiew derzeit seine Angriffe. Moskau sei sich "durchaus bewusst", dass infolge der Lieferungen und der Ankunft der ersten Kampfjets vom Typ F-16 "die Zeit zu unseren Gunsten spielen wird", erklärte de…
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Ukraine-Liveblog: ++ Putin entlässt vier Vize-Verteidigungsminister ++
Russlands Staatschef Putin hat vier stellvertretende Verteidigungsminister ihrer Ämter enthoben. Das ukrainische Militär meldet Erfolge gegen die Luftverteidigung auf der Krim. Alle Entwicklungen im Liveblog.

Hermitian-Einstein equations on noncompact manifolds
Di Wu, Xi Zhang
https://arxiv.org/abs/2406.11449 https://arxiv.org/pdf/2406.11449
arXiv:2406.11449v1 Announce Type: new
Abstract: This paper first investigates solvability of Hermitian-Einstein equation on a Hermitian holomorphic vector bundle on the complement of an arbitrary closed subset in a compact complex manifold. The uniqueness of Hermitian-Einstein metrics on a Zariski open subset in a compact K\"{a}hler manifold was only figured out by Takuro Mochizuki recently, the second part of this paper gives an affirmative answer to a question proposed by Takuro Mochizuki and based on which it leads to an alternative approach to the unique issue. We also prove stability from solvability of Hermitian-Einstein equation, which together with the classical existence result of Carlos Simpson in particular establish a Kobayashi-Hitchin bijective correspondence. The argument is also effective for uniqueness result and Kobayashi-Hitchin bijective correspondence on $\mathbb{C}$, as well as on non-K\"{a}hler and semi-stable contexts.

Tree Search for Simultaneous Move Games via Equilibrium Approximation
Ryan Yu, Alex Olshevsky, Peter Chin
https://arxiv.org/abs/2406.10411 https://arxiv.org/pdf/2406.10411
arXiv:2406.10411v1 Announce Type: new
Abstract: Neural network supported tree-search has shown strong results in a variety of perfect information multi-agent tasks. However, the performance of these methods on partial information games has generally been below competing approaches. Here we study the class of simultaneous-move games, which are a subclass of partial information games which are most similar to perfect information games: both agents know the game state with the exception of the opponent's move, which is revealed only after each agent makes its own move. Simultaneous move games include popular benchmarks such as Google Research Football and Starcraft.
In this study we answer the question: can we take tree search algorithms trained through self-play from perfect information settings and adapt them to simultaneous move games without significant loss of performance? We answer this question by deriving a practical method that attempts to approximate a coarse correlated equilibrium as a subroutine within a tree search. Our algorithm works on cooperative, competitive, and mixed tasks. Our results are better than the current best MARL algorithms on a wide range of accepted baseline environments.

Es war eine großartige Demo am Mo, 02.09.24 der antifaschistischen Mitmach-Kampagne "Den Rechten die Räume nehmen".
Unter dem Motto: "Keine Zusammenarbeit mit Faschist*innen – Feuer löschen statt Brandmauern" beteiligten sich mehrere hundert Menschen in #Osnabrück.
🙏🏻DANKE🙏🏻 an alle, die das möglich gemacht haben ‼️