Reinforcement Learning for Optimizing Automated Logic Gates
Abstract The optimization of logic gates plays a crucial role in Electronic Design Automation (EDA), typically managed by applying deterministic, rule-based heuristics to And-Inverter Graph (AIG) models of a circuit. As circuit complexity rises to billions of gates, these heuristic methods find it increasingly difficul...