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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 111–120 of 135 papers

TitleStatusHype
Avoiding Negative Side-Effects and Promoting Safe Exploration with Imaginative Planning—0
Learning Transferable Domain Priors for Safe Exploration in Reinforcement Learning—0
Linear Stochastic Bandits Under Safety Constraints—0
Data Efficient Reinforcement Learning for Legged Robots—0
Learning-based Model Predictive Control for Safe Exploration and Reinforcement LearningCode0
Robust Regression for Safe Exploration in Control—0
A Bayesian Approach to Robust Reinforcement Learning—0
Learning to Control Highly Accelerated Ballistic Movements on Muscular Robots—0
Efficient and Safe Exploration in Deterministic Markov Decision Processes with Unknown Transition Models—0
Temporal Logic Guided Safe Reinforcement Learning Using Control Barrier Functions—0
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