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...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Neurocomputing (Amsterdam) Jg. 515; S. 133 - 144
Hauptverfasser:	Gjærum, Vilde B., Strümke, Inga, Løver, Jakob, Miller, Timothy, Lekkas, Anastasios M.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.01.2023
Schlagworte:	Explainable artificial intelligence Model trees Reinforcement learning Robotics Explainable artificial intelligence Model trees Robotics Reinforcement learning
ISSN:	0925-2312, 1872-8286
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!