Compositional Policy Learning in Stochastic Control Systems with Formal Guarantees Ðor de Žikeli c

Reinforcement learning has shown promising results in learning neural network policies for complicated control tasks. However, the lack of formal guarantees about the behavior of such policies remains an impediment to their deployment.