Comparison of Reinforcement Learning Approaches for Automated Control Derivation in Design Space Exploration for Safety-Critical Automotive Applications
This paper explores reinforcement learning for automated control derivation within design space exploration with focus on a functional safety concept for safety-critical automotive applications. A multi-task reinforcement learning framework is proposed to handle optimal control for various system to...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Open Journal of Vehicular Technology |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11029148/ |
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