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This paper develops an approach to learn a policy of a dynamical system that is guaranteed to be both provably safe and goal-reaching.
A lyapunov-like characterization of asymptotic controllability
Eduardo D Sontag · 1983
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A smooth converse lyapunov theorem for robust stability
Yuandan Lin, Eduardo D Sontag, and Yuan Wang · 1996
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Nonlinear optimal control: A control lyapunov function and receding horizon perspective
James A Primbs, Vesna Nevistić, and John C Doyle · 1999
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Stephen Prajna, Antonis Papachristodoulou, and Pablo A Parrilo · 2002
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Stephen Prajna and Ali Jadbabaie · 2004
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Constructive safety using control barrier functions
Peter Wieland and Frank Allgöwer · 2007
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Set-theoretic methods in control
Franco Blanchini and Stefano Miani · 2008
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Playing atari with deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, and Martin Riedmiller · 2013
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Human-level control through deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A Rusu, Joel Veness, Marc G Bellemare, Alex Graves, Martin Riedmiller, Andreas K Fidjeland, Georg Ostrovski, et al · 2015
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Dario Amodei, Chris Olah, Jacob Steinhardt, Paul Christiano, John Schulman, and Dan Mané · 2016
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Control barrier function based quadratic programs for safety critical systems
Aaron D Ames, Xiangru Xu, Jessy W Grizzle, and Paulo Tabuada · 2016
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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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J Zico Kolter and Gaurav Manek · 2019
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Neural lyapunov control
Ya-Chien Chang, Nima Roohi, and Sicun Gao · 2019
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Learning control lyapunov functions from counterexamples and demonstrations
Hadi Ravanbakhsh and Sriram Sankaranarayanan · 2019
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Control barrier functions: Theory and applications
A. D. Ames, S. Coogan, M. Egerstedt, G. Notomista, K. Sreenath, and P. Tabuada · 2019
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Learning for safety-critical control with control barrier functions
Andrew Taylor, Andrew Singletary, Yisong Yue, and Aaron Ames · 2019
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End-to-end safe reinforcement learning through barrier functions for safety-critical continuous control tasks
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Richard S Sutton and Andrew G Barto · 2018
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The lyapunov neural network: Adaptive stability certification for safe learning of dynamical systems
Spencer M Richards, Felix Berkenkamp, and Andreas Krause · 2018
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A lyapunov-based approach to safe reinforcement learning
Yinlam Chow, Ofir Nachum, Edgar Duenez-Guzman, and Mohammad Ghavamzadeh · 2018
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Safe learning of quadrotor dynamics using barrier certificates
Li Wang, Evangelos A Theodorou, and Magnus Egerstedt · 2018
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The general problem of motion stability
Ao Mo Lyapunov
Cited in the paper.
Richard Cheng, Gábor Orosz, Richard M Murray, and Joel W Burdick · 2019
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Learning barrier functions for constrained motion planning with dynamical systems
Matteo Saveriano and Dongheui Lee · 2019
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Synthesis of control barrier functions using a supervised machine learning approach
Mohit Srinivasan, Amogh Dabholkar, Samuel Coogan, and Patricio Vela · 2020
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