Bidirectional Model-Based Policy Optimization Based on Adaptive Gaussian Noise and Improved Confidence Weights
Model-Based Reinforcement Learning (MBRL) has been gradually applied in the field of Robot Learning due to its excellent sample efficiency and asymptotic performance. However, for high-dimensional learning tasks in complex scenes, the exploration and stable training capabilities of the robot still n...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10225738/ |