Self-Learning Longitudinal Control for On-Road Vehicles
Reinforcement Learning is a promising tool to automate controller tuning. However, significant extensions are required for real-world applications to enable fast and robust learning. This work proposes several additions to the state of the art and proves their capability in a series of real world ex...
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| Main Author: | |
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| Format: | Electronic Book Chapter |
| Language: | English |
| Published: |
KIT Scientific Publishing
2023
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| Series: | Karlsruher Beiträge zur Regelungs- und Steuerungstechnik
20 |
| Subjects: | |
| Online Access: | OAPEN Library: download the publication OAPEN Library: description of the publication |
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| 520 | |a Reinforcement Learning is a promising tool to automate controller tuning. However, significant extensions are required for real-world applications to enable fast and robust learning. This work proposes several additions to the state of the art and proves their capability in a series of real world experiments. | ||
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| 546 | |a English | ||
| 650 | 7 | |a Electrical engineering |2 bicssc | |
| 653 | |a Regelungstechnik; Künstliche Intelligenz; Fahrzeugregelung; Längsdynamik; Bestärkendes Lernen; Control Theory; Artificial Intelligence; Vehicle Control; Longitudinal Dynamics; Reinforcement Learning | ||
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