@article{ae1d551e22ed47b1865c2a614be86efe,
title = "Deep Reinforcement Learning for Optimization at Early Design Stages",
abstract = "Deep reinforcement learning is shown to improve the design cost of hardware char63software interfaces within an industrial design framework. Based on optimization preferences specified by a designer, the proposed approach generates optimized solutions.",
keywords = "Combinatorial Optimization, Design Automation, Early Design Stages, Machine Learning, Reinforcement Learning",
author = "Lorenzo Servadei and Lee, {Jin Hwa} and Medina, {Jose A.Arjona} and Michael Werner and Sepp Hochreiter and Wolfgang Ecker and Robert Wille",
note = "Publisher Copyright: {\textcopyright} 2013 IEEE.",
year = "2023",
month = feb,
day = "1",
doi = "10.1109/MDAT.2022.3145344",
language = "English",
volume = "40",
pages = "43--51",
journal = "IEEE Design and Test",
issn = "2168-2356",
publisher = "IEEE Computer Society",
number = "1",
}