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.
Author supplied keywords
Cite
CITATION STYLE
APA
Servadei, L., Lee, J. H., Medina, J. A. A., Werner, M., Hochreiter, S., Ecker, W., & Wille, R. (2023). Deep Reinforcement Learning for Optimization at Early Design Stages. IEEE Design and Test, 40(1), 43–51. https://doi.org/10.1109/MDAT.2022.3145344
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
Already have an account? Sign in
Sign up for free