Reinforcement learning framework for the mechanical design of microelectronic components under multiphysics constraints

arXiv:2504.17142 · physics.comp-ph, cs.CE, cs.LG · Submitted 2025-04-23 · Read on arXiv

physics.comp-ph, cs.CE, cs.LG

Submitted: 2025-04-23

Updated: 2025-04-23

Terminology

• Actor — 28× in this paper · explained in 3 episodes
• Reinforcement Learning — 27× in this paper · explained in 4 episodes
• Accuracy — 17× in this paper · explained in 1 episode
• Q-learning — 14× in this paper · explained in 3 episodes
• Reward Function — 10× in this paper · explained in 2 episodes
• Inverse Design — 9× in this paper · explained in 2 episodes
• Reinforcement Learning (RL) — 8× in this paper · explained in 25 episodes
• Inverse Problem — 6× in this paper · explained in 2 episodes
• Actor-Critic Architecture — 5× in this paper · explained in 1 episode
• Deep Reinforcement Learning — 5× in this paper · explained in 2 episodes
• Objective Function — 5× in this paper · explained in 2 episodes
• Activation Function — 4× in this paper · explained in 1 episode
• Core — 4× in this paper · explained in 2 episodes
• Proximal Policy Optimization (PPO) — 4× in this paper · explained in 5 episodes
• Adam — 3× in this paper · explained in 2 episodes
• Action Space — 2× in this paper · explained in 1 episode
• Benchmark — 2× in this paper · explained in 2 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Loss Function — 2× in this paper · explained in 2 episodes
• Physical Constraints — 2× in this paper · explained in 7 episodes
• Active Learning — 1× in this paper · explained in 6 episodes
• Actor-Critic Model — 1× in this paper · explained in 1 episode
• Adjoint Method — 1× in this paper · explained in 1 episode
• Energy Efficiency — 1× in this paper · explained in 3 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Markov Decision Process (MDP) — 1× in this paper · explained in 11 episodes
• Physics-Informed Neural Network (PINN) — 1× in this paper · explained in 3 episodes
• Regularization — 1× in this paper · explained in 3 episodes

Sources

• Physics and geometry informed neural operator network with application to acoustic scattering
• Towards Machine Learning for Placement and Routing in Chip Design: a Methodological Overview
• An Actor-Critic Algorithm for Sequence Prediction
• Proximal Policy Optimization Algorithms

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