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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 81–90 of 135 papers

TitleStatusHype
Safe Exploration in Linear Equality Constraint—0
MetaDrive: Composing Diverse Driving Scenarios for Generalizable Reinforcement LearningCode2
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
Feasible Actor-Critic: Constrained Reinforcement Learning for Ensuring Statewise SafetyCode1
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
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