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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| Published in: | Neurocomputing (Amsterdam) Vol. 515; pp. 133 - 144 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier B.V
01.01.2023
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| Subjects: | |
| ISSN: | 0925-2312, 1872-8286 |
| Online Access: | Get full text |
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