Abstract Deep reinforcement learning (DRL) has become a dominant deep-learning paradigm for tasks where complex policies are learned within reactive systems. Unfortunately, these known to be susceptible bugs. Despite significant progress in DNN verification, there been little work demonstrating the use of modern verification tools on real-world, DRL-controlled In this case study, we attempt beg...