When I briefly used Cadence's stuff I always thought about how fixing DRC errors could be crowdsourced as an "idle game" because it's so puzzle-like. The other

When I briefly used Cadence's stuff I always thought about how fixing DRC errors could be crowdsourced as an "idle game" because it's so puzzle-like. The other thing was how it's even slower than Vivado... Using RL to automate DRC fixes, and modeling standard cells as graph/flow problems are things I'd love to learn more about. What papers would you recommend reading to get started (for a grad student already familiar with machine learning basics)?