A new MOX Report entitled “HypeMARL: Multi-Agent Reinforcement Learning For High-Dimensional, Parametric, and Distributed Systems” by Botteghi, N; Tomasetto, M; Fasel, U; Braghin, F; Manzoni, A has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/75-2026.pdf Abstract: Deep reinforcement learning has recently emerged as a promising feedback control […]
Daily Archives: October 7, 2026
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A new MOX Report entitled “Learning PDE solution operators with variable initial conditions via Latent Dynamics Networks” by Pizzamiglio, S.M.; Pagani, S.; Regazzoni, F. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/76-2026.pdf Abstract: In many-query scenarios, data-driven surrogate models provide an efficient alternative to high-fidelity solvers […]