2 papers
eess.SY2025
Data-assimilated model-informed reinforcement learning
Defne E. Ozan, Andrea Nóvoa, Georgios Rigas +1
The control of spatio-temporally chaos is challenging because of high dimensionality and unpredictability. Model-free reinforcement learning (RL) discovers optimal control policies…
nlin.CD2025
Real-time forecasting of chaotic dynamics from sparse data and autoencoders
Elise Ãzalp, Elise Özalp, Andrea Nóvoa +2
The real-time prediction of chaotic systems requires a nonlinear-reduced order model (ROM) to forecast the dynamics, and a stream of data from sensors to update the ROM. Data-drive…