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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 121–130 of 135 papers

Title	Date	Tasks	Status	Hype
Safety-Guided Deep Reinforcement Learning via Online Gaussian Process Estimation	Mar 6, 2019	Deep Reinforcement Learningreinforcement-learning	—Unverified	0
A predictive safety filter for learning-based control of constrained nonlinear dynamical systems	Dec 13, 2018	Model Predictive ControlReinforcement Learning	—Unverified	0
Safe Exploration in Markov Decision Processes with Time-Variant Safety using Spatio-Temporal Gaussian Process	Sep 12, 2018	Reinforcement LearningRobot Navigation	—Unverified	0
Safe Reinforcement Learning via Probabilistic Shields	Jul 16, 2018	Decision Makingreinforcement-learning	—Unverified	0
BubbleRank: Safe Online Learning to Re-Rank via Implicit Click Feedback	Jun 15, 2018	Learning-To-RankRe-Ranking	—Unverified	0
Virtuously Safe Reinforcement Learning	May 29, 2018	reinforcement-learningReinforcement Learning	—Unverified	0
Learning-based Model Predictive Control for Safe Exploration	Mar 22, 2018	modelModel Predictive Control	CodeCode Available	0
Safe Exploration in Continuous Action Spaces	Jan 26, 2018	Reinforcement LearningReinforcement Learning (RL)	CodeCode Available	1
Safe Exploration for Identifying Linear Systems via Robust Optimization	Nov 30, 2017	Reinforcement LearningReinforcement Learning (RL)	—Unverified	0
AI Safety Gridworlds	Nov 27, 2017	Deep Reinforcement Learningreinforcement-learning	CodeCode Available	0

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