Model tree methods for explaining deep reinforcement learning agents in real-time robotic applications

Deep reinforcement learning has shown useful in the field of robotics but the black-box nature of deep neural networks impedes the applicability of deep reinforcement learning agents for real-world tasks. This is addressed in the field of explainable artificial intelligence, by developing explanatio...

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Vydané v:	Neurocomputing (Amsterdam) Ročník 515; s. 133 - 144
Hlavní autori:	Gjærum, Vilde B., Strümke, Inga, Løver, Jakob, Miller, Timothy, Lekkas, Anastasios M.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.01.2023
Predmet:	Explainable artificial intelligence Model trees Reinforcement learning Robotics Explainable artificial intelligence Model trees Robotics Reinforcement learning
ISSN:	0925-2312, 1872-8286
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