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...

Optimization in layouts and robot motions is an essential yet challenging task for robotic cell systems crowded spaces. In the conventional research, since posture not explicitly considered, there may be no solution or operation time long if motion optimized layout obtained by arrangement optimization. this work, focusing on importance of posture, we propose a hierarchical optimization framewor...