This WP will be devoted to deriving strategies to control single systems via the combination of deep learning with control laws derived on a partial knowledge of the system to be controlled. Specifically, NA will focus on the extension of the CTQL strategy recently developed to control specific applications from Open AI Gym (e.g., inverted pendulum stabilization) by combining Q-Learning with state feedback control. Using expertise on deep learning and reinforcement learning from BO, a novel CTDL (control-tutored deep learning) algorithm will be synthesised at NA and validated at BO on a set of testbed problems selected from Open AI Gym.