Safety is essential for gaining trust in Markov Decision Process’s policies. We suggest a new method to improve safety, using Safe Zone. Given a policy, we define its Safe Zone as a subset of states, such that most of the policy’s trajectories are confined to this subset. A trajectory not entirely inside the Safe Zone is potentially unsafe and should be examined. The quality of the Safe Zone is parameterized by the number of states and the escape probability, i.e., the probability that a random…