Safe DNN-type Controller Synthesis for Nonlinear Systems via Meta Reinforcement Learning

There is a pressing need to synthesize provable safety controllers for nonlinear systems as they are embedded in many safety-critical applications. In this paper, we propose a safe Meta Reinforcement Learning (Meta-RL) approach to synthesize deep neural network (DNN) controllers for nonlinear system...

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Bibliographic Details

Published in:	2023 60th ACM/IEEE Design Automation Conference (DAC) pp. 1 - 6
Main Authors:	Zhao, Hanrui, Zeng, Xia, Qi, Niuniu, Yang, Zhengfeng, Zeng, Zhenbing
Format:	Conference Proceeding
Language:	English
Published:	IEEE 09.07.2023
Subjects:	Artificial neural networks Benchmark testing controller synthesis formal verification meta learning Metalearning Pressing Reinforcement learning Safety Training
Online Access:	Get full text
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