V-OCBF: Learning Safety Filters from Offline Data via Value-Guided Offline Control Barrier Functions
Published:Dec 11, 2025 17:14
•1 min read
•ArXiv
Analysis
This article introduces a novel approach, V-OCBF, for learning safety filters using offline data. The method leverages value-guided offline control barrier functions, suggesting an innovative way to address safety concerns in AI systems trained on pre-existing datasets. The focus on offline data is particularly relevant as it allows for safer experimentation and deployment in real-world scenarios. The title clearly indicates the core methodology and its application.
Key Takeaways
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