A data-driven framework synthesizes stochastic control barrier certificates and safety controllers for unknown polynomial stochastic systems, with probabilistic safety guarantees and certified confidence from multiple noisy trajectories.
Model-based reinforcement learning: A survey,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
eess.SY 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
Data-Driven Stochastic Control: Foundations and Guarantees
A data-driven framework synthesizes stochastic control barrier certificates and safety controllers for unknown polynomial stochastic systems, with probabilistic safety guarantees and certified confidence from multiple noisy trajectories.