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20152019
most citedVirtual vs. Real: Trading Off Simulations and Physical Experiments in Reinforcement Learning with Bayesian Optimization

114 citations · 321 across the 8 of their papers we have counts for

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cs.LG2019★ 1 cited

Trajectory-Based Off-Policy Deep Reinforcement Learning

Andreas Doerr, Michael Volpp, Marc Toussaint +2

Policy gradient methods are powerful reinforcement learning algorithms and have been demonstrated to solve many complex tasks. However, these methods are also data-inefficient, aff…

cs.LG2017

Model-Based Policy Search for Automatic Tuning of Multivariate PID Controllers

Andreas Doerr, Duy Nguyen-Tuong, Alonso Marco +2

PID control architectures are widely used in industrial applications. Despite their low number of open parameters, tuning multiple, coupled PID controllers can become tedious in pr…