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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 71–80 of 135 papers

TitleStatusHype
Safe Exploration Using Bayesian World Models and Log-Barrier Optimization—0
Safe Interactive Model-Based Learning—0
Safe model-based design of experiments using Gaussian processes—0
Safe Reinforcement Learning in a Simulated Robotic Arm—0
Safe Reinforcement Learning of Dynamic High-Dimensional Robotic Tasks: Navigation, Manipulation, Interaction—0
Safe Reinforcement Learning via Shielding under Partial Observability—0
Safe Reinforcement Learning with Contrastive Risk Prediction—0
Safe Reinforcement Learning with Dead-Ends Avoidance and Recovery—0
Safety-Guided Deep Reinforcement Learning via Online Gaussian Process Estimation—0
Safety Representations for Safer Policy Learning—0
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