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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 126–135 of 135 papers

TitleStatusHype
Handling Long-Term Safety and Uncertainty in Safe Reinforcement LearningCode0
Benefits of Monotonicity in Safe Exploration with Gaussian ProcessesCode0
Safe Reinforcement Learning in Black-Box Environments via Adaptive ShieldingCode0
DOPE: Doubly Optimistic and Pessimistic Exploration for Safe Reinforcement LearningCode0
Exterior Penalty Policy Optimization with Penalty Metric Network under ConstraintsCode0
Enforcing Almost-Sure Reachability in POMDPsCode0
Curiosity Killed or Incapacitated the Cat and the Asymptotically Optimal AgentCode0
Safe Exploration Method for Reinforcement Learning under Existence of DisturbanceCode0
Probabilistic Counterexample Guidance for Safer Reinforcement Learning (Extended Version)Code0
A comparison of RL-based and PID controllers for 6-DOF swimming robots: hybrid underwater object trackingCode0
Show:102550
← PrevPage 6 of 6Next →

No leaderboard results yet.