Deep Reinforcement Learning for Optimization at Early Design Stages
Lorenzo Servadei, Jin Hwa Lee, Jose A. Arjona-Medina, Michael Werner, Sepp Hochreiter, Wolfgang Ecker, Robert Wille · IEEE Design and Test · 2022
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.