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 91–100 of 135 papers

TitleStatusHype
Safety-Critical Learning of Robot Control with Temporal Logic Specifications—0
Bayesian Controller Fusion: Leveraging Control Priors in Deep Reinforcement Learning for Robotics—0
Safe Exploration by Solving Early Terminated MDP—0
Learning Policies with Zero or Bounded Constraint Violation for Constrained MDPs—0
Safe Exploration in Model-based Reinforcement Learning using Control Barrier Functions—0
Safe Continuous Control with Constrained Model-Based Policy OptimizationCode0
Towards Safe Continuing Task Reinforcement Learning—0
Safe model-based design of experiments using Gaussian processes—0
Conservative Safety Critics for Exploration—0
Data-efficient visuomotor policy training using reinforcement learning and generative models—0
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