Name
Abstract | ||
|---|---|---|
Reinforcement learning (RL) methods have demonstrated their efficiency in simulation. However, many of the applications for which RL offers great potential, such as autonomous driving, are also safety critical and require a certified closed-loop behavior in order to meet the safety specifications in the presence of physical constraints. This article introduces a concept called probabilistic model ... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TAC.2021.3049335 | IEEE Transactions on Automatic Control |
Keywords | DocType | Volume |
Safety,Predictive models,Probabilistic logic,Predictive control,Prediction algorithms,Optimization,Uncertainty | Journal | 67 |
Issue | ISSN | Citations |
1 | 0018-9286 | 1 |
PageRank | References | Authors |
0.35 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kim Peter Wabersich | 1 | 3 | 2.42 |
| Lukas Hewing | 2 | 25 | 4.27 |
| Carron, A. | 3 | 28 | 4.97 |
| Melanie Nicole Zeilinger | 4 | 298 | 30.91 |