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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 126–135 of 135 papers

Title	Date	Tasks	Status	Hype
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
Decoupled Learning of Environment Characteristics for Safe Exploration	Aug 9, 2017	reinforcement-learningReinforcement Learning	—Unverified	0
Concrete Problems in AI Safety	Jun 21, 2016	BIG-bench Machine LearningSafe Exploration	CodeCode Available	0
Safe Exploration in Finite Markov Decision Processes with Gaussian Processes	Jun 15, 2016	Gaussian ProcessesReinforcement Learning	CodeCode Available	0
Safe Exploration of State and Action Spaces in Reinforcement Learning	Feb 4, 2014	Efficient ExplorationManagement	—Unverified	0
Safe Exploration in Markov Decision Processes	May 22, 2012	Safe Exploration	—Unverified	0

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