Safe Reinforcement Learning Using Robust MPC

Reinforcement learning (RL) has recently impressed the world with stunning results in various applications. While the potential of RL is now well established, many critical aspects still need to be tackled, including safety and stability issues. These issues, while secondary for the RL community, ar...

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Bibliographic Details

Published in:	IEEE transactions on automatic control Vol. 66; no. 8; pp. 3638 - 3652
Main Authors:	Zanon, Mario, Gros, Sebastien
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.08.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Computational modeling Data models Learning Model accuracy Numerical models Optimization Predictive control Reinforcement learning (RL) robust model predictive control (MPC) Robustness Robustness (mathematics) safe policies Safety Stability analysis Uncertainty
ISSN:	0018-9286, 1558-2523
Online Access:	Get full text
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