5 citations · 5 across the 6 of their papers we have counts for
3 papers · 1 filter
LGML: Logic Guided Machine Learning
Joseph Scott, Maysum Panju, Vijay Ganesh
We introduce Logic Guided Machine Learning (LGML), a novel approach that symbiotically combines machine learning (ML) and logic solvers with the goal of learning mathematical funct…
Effective problem solving using SAT solvers
Curtis Bright, Jürgen Gerhard, Ilias Kotsireas +1
In this article we demonstrate how to solve a variety of problems and puzzles using the built-in SAT solver of the computer algebra system Maple. Once the problems have been encode…
Relating Complexity-theoretic Parameters with SAT Solver Performance
Edward Zulkoski, Ruben Martins, Christoph Wintersteiger +4
Over the years complexity theorists have proposed many structural parameters to explain the surprising efficiency of conflict-driven clause-learning (CDCL) SAT solvers on a wide va…