Automated Design of Complex Analog Circuits with Multiagent based Reinforcement Learning

Despite the effort of analog circuit design automation, currently complex analog circuit design still requires extensive manual iterations, making it labor intensive and time-consuming. Recently, reinforcement learning (RL) algorithms have been demonstrated successfully for the analog circuit design...

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Veröffentlicht in:	2023 60th ACM/IEEE Design Automation Conference (DAC) S. 1 - 6
Hauptverfasser:	Zhang, Jinxin, Bao, Jiarui, Huang, Zhangcheng, Zeng, Xuan, Lu, Ye
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 09.07.2023
Schlagworte:	Analog circuits Circuit design automation Circuit stability Complex analog circuits Design automation Manuals Multiagent reinforcement learning Reinforcement learning Topology Training Twin delayed deep deterministic policy gradient
Online-Zugang:	Volltext
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