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

Kun Dong, Yongle Luo, Erkang Cheng, Zhiyong Sun, Lili Zhao, Qiang Zhang, Chao Zhou, Bo Song. Balance Between Efficient and Effective Learning: Dense2Sparse Reward Shaping for Robot Manipulation with Environment Uncertainty. In IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2022, Sapporo, Japan, July 11-15, 2022. pages 1192-1198, IEEE, 2022. [doi]

@inproceedings{DongLCSZZZS22,
  title = {Balance Between Efficient and Effective Learning: Dense2Sparse Reward Shaping for Robot Manipulation with Environment Uncertainty},
  author = {Kun Dong and Yongle Luo and Erkang Cheng and Zhiyong Sun and Lili Zhao and Qiang Zhang and Chao Zhou and Bo Song},
  year = {2022},
  doi = {10.1109/AIM52237.2022.9863259},
  url = {https://doi.org/10.1109/AIM52237.2022.9863259},
  researchr = {https://researchr.org/publication/DongLCSZZZS22},
  cites = {0},
  citedby = {0},
  pages = {1192-1198},
  booktitle = {IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2022, Sapporo, Japan, July 11-15, 2022},
  publisher = {IEEE},
  isbn = {978-1-6654-1308-4},
}