Curriculum learning for robotic agents
Model-free deep RL algorithms, rooted in the concept of tabula rasa, suffer from poor sample efficiency, which is a major drawback for these methods to be applicable to real-world robotics problems. To improve sample efficiency, curriculum learning leverages prior knowledge in a way to solve diff...
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Thesis-Doctor of Philosophy |
| Language: | English |
| Published: |
Nanyang Technological University
2022
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/160311 |