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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

Showing 76100 of 135 papers

TitleStatusHype
Safe Reinforcement Learning via Shielding under Partial Observability0
Safe Reinforcement Learning with Contrastive Risk Prediction0
Safe Reinforcement Learning with Dead-Ends Avoidance and Recovery0
Safety-Guided Deep Reinforcement Learning via Online Gaussian Process Estimation0
Safety Representations for Safer Policy Learning0
Sample-efficient Safe Learning for Online Nonlinear Control with Control Barrier Functions0
SCOPE: Safe Exploration for Dynamic Computer Systems Optimization0
Safe Reinforcement Learning via Probabilistic Shields0
SLAC: Simulation-Pretrained Latent Action Space for Whole-Body Real-World RL0
System III: Learning with Domain Knowledge for Safety Constraints0
Temporal Logic Guided Safe Reinforcement Learning Using Control Barrier Functions0
Towards Safe Continuing Task Reinforcement Learning0
Towards Safe Load Balancing based on Control Barrier Functions and Deep Reinforcement Learning0
Towards Socially and Morally Aware RL agent: Reward Design With LLM0
Training and Evaluation of Deep Policies using Reinforcement Learning and Generative Models0
Trajectory-wise Iterative Reinforcement Learning Framework for Auto-bidding0
A Safe Exploration Strategy for Model-free Task Adaptation in Safety-constrained Grid Environments0
Virtuously Safe Reinforcement Learning0
A Bayesian Approach to Robust Reinforcement Learning0
Ablation Study of How Run Time Assurance Impacts the Training and Performance of Reinforcement Learning Agents0
ActSafe: Active Exploration with Safety Constraints for Reinforcement Learning0
A Human-Centered Safe Robot Reinforcement Learning Framework with Interactive Behaviors0
Approximate Shielding of Atari Agents for Safe Exploration0
A Safe Self-evolution Algorithm for Autonomous Driving Based on Data-Driven Risk Quantification Model0
A Safe Semi-supervised Graph Convolution Network0
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