SOTAVerified

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 51–60 of 135 papers

TitleStatusHype
Safe Reinforcement Learning with Dead-Ends Avoidance and Recovery—0
Provably Learning Nash Policies in Constrained Markov Potential Games—0
Exploration of Unranked Items in Safe Online Learning to Re-Rank—0
System III: Learning with Domain Knowledge for Safety Constraints—0
Approximate Shielding of Atari Agents for Safe Exploration—0
Safe and Sample-efficient Reinforcement Learning for Clustered Dynamic EnvironmentsCode0
A Human-Centered Safe Robot Reinforcement Learning Framework with Interactive Behaviors—0
Information-Theoretic Safe Exploration with Gaussian ProcessesCode0
Benefits of Monotonicity in Safe Exploration with Gaussian ProcessesCode0
Atlas: Automate Online Service Configuration in Network SlicingCode0
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