news    views    talk    learn    |    about    contribute     republish     crowdfunding     archives     events

Peter Stone: Robot Skill Learning: From the Real World to Simulation and Back | CMU RI Seminar


curated by | April 2, 2017

Link to video on YouTube

Abstract: “For autonomous robots to operate in the open, dynamically changing world, they will need to be able to learn a robust set of interacting skills. This talk begins by introducing “Overlapping Layered Learning” as a novel hierarchical machine learning paradigm for learning such interacting skills in simulation. While learning in simulation is appealing because it avoids the prohibitive sample cost of learning in the real world, unfortunately policies learned in simulation often fail when applied on physical robots. This talk then introduces “Grounded Simulation Learning” to address this problem by algorithmically altering the simulator to better match the real world, and connects this new algorithm to a theoretical analysis of off-policy evaluation in reinforcement learning. Overlapping Layered Learning was the key deciding factor in UT Austin Villa’s RoboCup robot soccer 3D simulation league championship, and Grounded Simulation Learning has led to the fastest known stable walk on a widely used humanoid robot.”

-->

Other articles on similar topics:


comments powered by Disqus


Kickstart Accelerator
April 17, 2017

Are you planning to crowdfund your robot startup?

Need help spreading the word?

Join the Robohub crowdfunding page and increase the visibility of your campaign