Mask-Attention A3C: Visual Explanation of Action–State Value in Deep Reinforcement Learning

Deep reinforcement learning (DRL) can learn an agent’s optimal behavior from the experience it gains through interacting with its environment. However, since the decision-making process of DRL agents is a black-box, it is difficult for users to understand the reasons for the agents’ ac...

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Autores principales:	Hidenori Itaya, Tsubasa Hirakawa, Takayoshi Yamashita, Hironobu Fujiyoshi, Komei Sugiura
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	IEEE 2024-01-01
Colección:	IEEE Access
Materias:	Deep reinforcement learning explainable AI visual explanation video games robot manipulation
Acceso en línea:	https://ieeexplore.ieee.org/document/10560007/
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