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Safe Exploration

Safe Exploration is an approach to collect ground truth data by safely interacting with the environment.

Source: Chance-Constrained Trajectory Optimization for Safe Exploration and Learning of Nonlinear Systems

Papers

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Showing 101–110 of 135 papers

TitleStatusHype
SafeML: Safety Monitoring of Machine Learning Classifiers through Statistical Difference MeasureCode1
Chance-Constrained Trajectory Optimization for Safe Exploration and Learning of Nonlinear Systems—0
Safe deep reinforcement learning-based constrained optimal control scheme for active distribution networks—0
Learning-based Symbolic Abstractions for Nonlinear Control Systems—0
Provably Efficient Safe Exploration via Primal-Dual Policy Optimization—0
Safe reinforcement learning for probabilistic reachability and safety specifications: A Lyapunov-based approachCode0
Safe Exploration for Optimizing Contextual BanditsCode0
Safe Interactive Model-Based Learning—0
Safe Exploration for Interactive Machine Learning—0
Building HVAC Scheduling Using Reinforcement Learning via Neural Network Based Model Approximation—0
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