Predicting before acting: improving policy quality by taking a vision of consequence
Deep reinforcement learning has achieved great success in many fields. However, the agent may get trapped during the exploration, lingering around feckless states that pull the agent away from optimal policies. Thus it's worth studying how to improve learning strategies by forecasting future st...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2022-12-01
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| Series: | Connection Science |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/09540091.2022.2025765 |