A NN algorithm for Boolean satisfiability problems
William M. Spears · 2002
Satisfiability (SAT) refers to the task of finding a truth assignment that makes an arbitrary Boolean expression true. This paper compares a neural network algorithm (NNSAT) with GSAT, a greedy algorithm for solving satisfiability problems. GSAT can solve problem instances that are difficult for traditional satisfiability algorithms. Results suggest that NNSAT scales better as the number of variables increase, solving at least as many hard SAT problems.