Learning robust policies for uncertain parametric Markov decision processes
Synthesising verifiably correct controllers for dynamical systems is crucial for safety-critical problems. To achieve this, it is important to account for uncertainty in a robust manner, while at the same time it is often of interest to avoid being overly conservative with the view of achieving a be...
| Main Authors: | , , |
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| Format: | Conference item |
| Language: | English |
| Published: |
Journal of Machine Learning Research
2024
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