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Distributionally Safe Reinforcement Learning under Model Uncertainty: A Single-Level Approach by Differentiable Convex Programming
This end-to-end differentiable framework with safety constraints, to the best of our knowledge, is the first tractable single-level solution to address distributional safety.
Wasserstein Distributionally Robust Control Barrier Function using Conditional Value-at-Risk with Differentiable Convex Programming
Control Barrier functions (CBFs) have attracted extensive attention for designing safe controllers for their deployment in real-world safety-critical systems.
On the Optimality, Stability, and Feasibility of Control Barrier Functions: An Adaptive Learning-Based Approach
Safety has been a critical issue for the deployment of learning-based approaches in real-world applications.
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