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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 41–50 of 135 papers

TitleStatusHype
A Safe Self-evolution Algorithm for Autonomous Driving Based on Data-Driven Risk Quantification Model—0
Highway Value Iteration Networks—0
A Safe Semi-supervised Graph Convolution Network—0
Information-Theoretic Safe Bayesian Optimization—0
Exploration in Deep Reinforcement Learning: A Survey—0
A safe exploration approach to constrained Markov decision processes—0
BubbleRank: Safe Online Learning to Re-Rank via Implicit Click Feedback—0
Approximate Shielding of Atari Agents for Safe Exploration—0
Learning-based Symbolic Abstractions for Nonlinear Control Systems—0
Learning Human-like Representations to Enable Learning Human Values—0
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