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Safety remains a central obstacle preventing widespread use of RL in the real world: learning new tasks in uncertain environments requires extensive exploration, but safety requires limiting exploration.
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“Safe Exploration in Finite Markov Decision Processes with Gaussian Processes”
Matteo Turchetta, Felix Berkenkamp and Andreas Krause · 2016
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Joshua Achiam, David Held, Aviv Tamar and Pieter Abbeel · 2017
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Somil Bansal, Mo Chen, Sylvia Herbert and Claire. Tomlin · 2017
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“Safe Model-based Reinforcement Learning with Stability Guarantees”
Felix Berkenkamp, Matteo Turchetta, Angela. Schoellig and Andreas Krause · 2017
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“Safe Reinforcement Learning via Shielding”
Mohammed Alshiekh et al · 2018
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“A Lyapunov-based Approach to Safe Reinforcement Learning”
Y. Chow, O. Nachum, E. Duéñez-Guzmán and M. Ghavamzadeh · 2018
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“Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models”
Kurtland Chua, Roberto Calandra, Rowan McAllister and Sergey Levine · 2018
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“Visual Foresight: Model-Based Deep Reinforcement Learning for Vision-Based Robotic Control”
Frederik Ebert et al · 2018
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“Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning”
“Deep Dynamics Models for Learning Dexterous Manipulation”
Anusha Nagabandi, Kurt Konoglie, Sergey Levine and Vikash Kumar · 2019
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“Benchmarking Safe Exploration in Deep Reinforcement Learning”
Alex Ray, Joshua Achiam and Dario Amodei · 2019
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“Worst Cases Policy Gradients”
Yichuan Tang, Jian Zhang and Ruslan Salakhutdinov · 2019
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“Reward Constrained Policy Optimization”
Chen Tessler, Daniel. Mankowitz and Shie Mannor · 2019
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“Efficiently Calibrating Cable-Driven Surgical Robots With RGBD Sensing, Temporal Windowing, and Linear and Recurrent Neural Network Compensation”
Minho Hwang et al · 2020
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“Robust Model Predictive Shielding for Safe Reinforcement Learning with Stochastic Dynamics”
Shuo Li and Osbert Bastani · 2020
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Benjamin Eysenbach, Shixiang Gu, Julian Ibarz and Sergey Levine · 2018
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“A General Safety Framework for Learning-Based Control in Uncertain Robotic Systems”
Jaime. Fisac et al · 2018
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“Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor”
Tuomas Haarnoja, Aurick Zhou, Pieter Abbeel and Sergey Levine · 2018
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“Soft Actor-Critic Algorithms and Applications”
Tuomas Haarnoja et al · 2018
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“QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation”
Dmitry Kalashnikov et al · 2018
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“Learning Model Predictive Control for Iterative Tasks. A Data-Driven Control Framework”
Ugo Rosolia and Francesco Borrelli · 2018
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“Lyapunov-based Safe Policy Optimization for Continuous Control”
Y. Chow et al · 2019
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“Goal-Aware Prediction: Learning to Model What Matters”
Suraj Nair, Silvio Savarese and Chelsea Finn · 2020
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Krishnan Srinivasan et al · 2020
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Pranjal Tandon · 2020
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“ABC-LMPC: Safe Sample-Based Learning MPC for Stochastic Nonlinear Dynamical Systems with Adjustable Boundary Conditions”
Brijen Thananjeyan et al · 2020
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Brijen Thananjeyan et al · 2020
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Quan Vuong · 2020
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