Combined Constraint on Behavior Cloning and Discriminator in Offline Reinforcement Learning
In recent years, reinforcement learning (RL) has received a lot of attention because we can automatically learn optimal behavioral policies. However, since RL acquires the policy by repeatedly interacting with the environment, it is difficult to learn about realistic tasks. In recent years, there ha...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10418100/ |