… With deep reinforcement learning (RL) methods achieving results that exceed human
capabilities in games, robotics, and simulated environments, continued scaling of RL …

… The authors developed a decentralized implementation to evolve agents in distributed …
a population-based reinforcement learning (PBRL) framework in robotics that allows the …

… GPU-accelerated simulation tailored towards learning algorithms. Isaac Gym was developed
to maximize the throughput of physics-based machine learning … Gaussian distribution with …

… This parallelism allows large robots or multiple reinforcement learning agents to be … robotics
applications, few attempts have been made to develop GPU accelerated robotics simulation …

… Large scale GPU accelerated physics are executed with thousands of robots in parallel. …
once chosen, is transformed to the 3D camera frame and stitches are distributed evenly [35]. …

… the means to simulate one or more … for training agents via deep reinforcement learning.
We also provide interface packages for the Robotic Operating System (ROS1) and the Robotic …

… Imitation and Reinforcement Learning We aim to … The state-action marginal of the trajectory
distribution induced by a … Lastly, our results showed that DAPG on GPU-accelerated RL …

… reinforcement learning applications compared to the alternatives: 1) the modular architecture
enables using the simulator … ; 3) the new distributed simulation capability allows simulating …

… Realistic GPU-accelerated simulators and engines have been proposed. Isaac [17] is a
proprietary NVIDIA simulator used for realistic robotic simulation in reinforcement learning. …

… complex dexterous manipulation with deep reinforcement learning and demonstrations,”
RSS, … Fox, “GPU-accelerated robotic simulation for distributed reinforcement learning,” CoRL, …