NeurIPS 2020

Can Q-Learning with Graph Networks Learn a Generalizable Branching Heuristic for a SAT Solver?

Meta Review

The paper describes a new branching heuristic based on GNNs with DQNs. This is novel and promising. From a SAT perspective, the approach is not compared to the state of the art, but it provides a useful proof of concept that illustrates how GNNs and DQNs can be used to reduce the number of iterations of the branching heuristic. Due to the high computational cost of GNNs and DQNs this does not translate into a reduction in computation time, but the ideas are still useful and promising.