Model-based Reinforcement Learning with Neural Network Dynamics

A learned neural network dynamics model enables a hexapod robot to learn to run and follow desired trajectories, using just 17 minutes of real-world experience. Enabling robots to act autonomously in the real-world is difficult. Even with expensive robots and teams of world-class researchers, robots still have difficulty autonomously navigating and interacting in complex, unstructured environments. Why are autonomous robots not out in the world among us? Engineering systems that can cope with all the complexities of our world is hard.