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and Peter Stone

1 accepted papers

2020

Stochastic Grounded Action Transformation for Robot Learning in Simulation

IROS 2020poster

Robot control policies learned in simulation do not often transfer well to the real world. Many existing solutions to this sim-to-real problem, such as the Grounded Action Transformation (GAT) algorithm, seek to correct for- or ground-these differences by matching the simulator to the real world. Ho…

Cited by 30SourceScholar