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Balance Between Efficient and Effective Learning: Dense2Sparse Reward
  Shaping for Robot Manipulation with Environment Uncertainty

Balance Between Efficient and Effective Learning: Dense2Sparse Reward Shaping for Robot Manipulation with Environment Uncertainty

5 March 2020
Yongle Luo
Kun Dong
Lili Zhao
Zhiyong Sun
Chao Zhou
Bo Song
ArXivPDFHTML

Papers citing "Balance Between Efficient and Effective Learning: Dense2Sparse Reward Shaping for Robot Manipulation with Environment Uncertainty"

2 / 2 papers shown
Title
Emergence of Locomotion Behaviours in Rich Environments
Emergence of Locomotion Behaviours in Rich Environments
N. Heess
TB Dhruva
S. Sriram
Jay Lemmon
J. Merel
...
Tom Erez
Ziyun Wang
S. M. Ali Eslami
Martin Riedmiller
David Silver
118
927
0
07 Jul 2017
Transferring End-to-End Visuomotor Control from Simulation to Real World
  for a Multi-Stage Task
Transferring End-to-End Visuomotor Control from Simulation to Real World for a Multi-Stage Task
Stephen James
Andrew J. Davison
Edward Johns
162
275
0
07 Jul 2017
1