Hierarchical Reinforcement Learning: A Survey and Open Research Challenges
Reinforcement learning (RL) allows an agent to solve sequential decision-making problems by interacting with an environment in a trial-and-error fashion. When these environments are very complex, pure random exploration of possible solutions often fails, or is very sample inefficient, requiring an u...
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| Автори: | , , |
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| Формат: | Artigo |
| Мова: | Inglês |
| Опубліковано: |
MDPI AG
2022-02-01
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| Серія: | Machine Learning and Knowledge Extraction |
| Предмети: | |
| Онлайн доступ: | https://www.mdpi.com/2504-4990/4/1/9 |
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