… This set of examples shows that the proposed challenges appear in … challenges, reinforcement
learning can be more readily used to solve many of these important real-world problems. …

… challenges that appear when using RL on real world systems. Not all of these challenges
will be present in every real system, but in many cases all of the challenges are present to …

… This set of examples shows that the proposed challenges appear in … challenges, reinforcement
learning can be more readily used to solve many of these important real-world problems. …

… autonomous learning. We give a summary of the state-of-the-art of reinforcement learning in
the … Numerous challenges faced by the policy representation in robotics are identified. Three …

… the existing challenges in deep reinforcement learning research … efficiency problem; (2)
stability of training; (3) the catastrophic … the real world; (8) large-scale reinforcement learning with …

… real world reinforcement learning without instrumentation. However, when utilized for robotic
learning problems… extend to several other tasks, including real world tasks, in Section 6. The …

… to reinforcement learning (RL), and its relationship with deep learning, machine learning and
AI. … It is desirable to have RL systems that work in the real world with real benefits. However, …

… difficulties, we introduce six reinforcement learning tasks based on three commercially available
robots. Most of these tasks … these tasks, we compare and benchmark four reinforcement …

… challenges for real life reinforcement learning (RL) control, here we propose a non-exhaustive
set of nine real world challenges for … implemented in real world problems. Comparisons …

… reinforcement learning approach, but also the importance of fast online adaptation in the
real world, … While we focus on reinforcement learning problems in our experiments, this meta-…