This Robot used Dreamer Algorithm to learn walking in 60 minutes

A team of researchers from the University of California, Berkeley, have introduced an approach to teaching robots how to walk in under 60 minutes. This technique is different from the conventional deep reinforcement learning practices in a way that in this technique, robots can be trained without simulators. Named "DayDreamer: World Models for Physical Robot Learning", this project is led by Philipp Wu, Alejandro Escontrela, Danijar Hafner, Ken Goldberg and Pieter Abbeel. As per the authors, the Dreamer algorithm could learn from small amounts of interaction through planning in a learned world model and, in turn, outperform pure reinforcement learning in video games. One of the fundamental challenges that robotics has struggled with is imbibing in robots the capability to solve complex tasks in real-world scenarios.