Safe reinforcement learning in automotive
This work applies Logically Constrained Reinforcement Learning (LCRL) frame-work for synthesizing policies for active monitoring and management of sensor modules in autonomous vehicles. LCRL allows synthesizing policies for unknown and continuous-state Markov Decision Processes (MDPs) such that a gi...
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| Format: | Thesis |
| Language: | English |
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2020
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