NAEM: Noisy Attention Exploration Module for Deep Reinforcement Learning
Recently, deep reinforcement learning (RL) has been a hot topic due to its high capability in solving complex decision-making tasks. Although deep RL has achieved remarkable results in many fields, efficient exploration remains one of its most challenging issues. Conventional exploration heuristic m...
Guardado en:
Autores principales: | Zhenwen Cai, Feifei Lee, Chunyan Hu, Koji Kotani, Qiu Chen |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
IEEE
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/2f304b4eae664799bacde718e8aa78b3 |
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