Identifying Policy Gradient Subspaces

no code implementations • 12 Jan 2024 • Jan Schneider, Pierre Schumacher, Simon Guist, Le Chen, Daniel Häufle, Bernhard Schölkopf, Dieter Büchler

Policy gradient methods hold great potential for solving complex continuous control tasks.

Continuous Control Policy Gradient Methods +1

Hindsight States: Blending Sim and Real Task Elements for Efficient Reinforcement Learning

no code implementations • 3 Mar 2023 • Simon Guist, Jan Schneider, Alexander Dittrich, Vincent Berenz, Bernhard Schölkopf, Dieter Büchler

Reinforcement learning has shown great potential in solving complex tasks when large amounts of data can be generated with little effort.

reinforcement-learning Reinforcement Learning (RL)

Learning to Play Table Tennis From Scratch using Muscular Robots

no code implementations • 10 Jun 2020 • Dieter Büchler, Simon Guist, Roberto Calandra, Vincent Berenz, Bernhard Schölkopf, Jan Peters

This work is the first to (a) fail-safe learn of a safety-critical dynamic task using anthropomorphic robot arms, (b) learn a precision-demanding problem with a PAM-driven system despite the control challenges and (c) train robots to play table tennis without real balls.

reinforcement-learning Reinforcement Learning (RL)