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1 Ergebnisse
1
A Reinforcement Learning Agent for Obstacle-Avoiding Rectil..:
, In:
Proceedings of the 2022 International Symposium on Physical Design
,
Chen, Po-Yan
;
Ke, Bing-Ting
;
Lee, Tai-Cheng
... - p. 107-115 , 2022
Link:
https://dl.acm.org/doi/10.1145/3505170.3506721
RT T1 <cTitle>Proceedings of the 2022 International Symposium on Physical Design</cTitle>: T1 <Title>A Reinforcement Learning Agent for Obstacle-Avoiding Rectilinear Steiner Tree Construction</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3506721&Exemplar=1&LAN=DE A1 Chen, Po-Yan A1 Ke, Bing-Ting A1 Lee, Tai-Cheng A1 Tsai, I-Ching A1 Kung, Tai-Wei A1 Lin, Li-Yi A1 Liu, En-Cheng A1 Chang, Yun-Chih A1 Li, Yih-Lang A1 Chao, Mango C.-T. PB ACM YR 2022 K1 monte carlo tree search K1 obstacle-avoiding rectilinear steiner tree K1 reinforcement learning K1 steiner point prediction K1 Hardware K1 Electronic design automation K1 Physical design (EDA) K1 Wire routing K1 Computing methodologies K1 Machine learning K1 Learning paradigms K1 Reinforcement learning SP 107 OP 115 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3505170.3506721 DO https://dl.acm.org/doi/10.1145/3505170.3506721 SF ELIB - SuUB Bremen
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