Enhancing sample efficiency in reinforcement-learning-based flow control: replacing the critic with an adaptive reduced-order model

Researchers replace neural critics with adaptive reduced-order models in reinforcement learning for fluid dynamics, dramatically cutting training data needs and computational cost.