  Nieuwenhuis, Oliveras, and Tinelli (2006) showed how to describe enhancements
of the Davis-Putnam-Logemann-Loveland algorithm using transition systems,
instead of pseudocode. We design a similar framework for several algorithms
that generate answer sets for logic programs: Smodels, Smodels-cc, Asp-Sat with
Learning (Cmodels), and a newly designed and implemented algorithm Sup. This
approach to describing answer set solvers makes it easier to prove their
correctness, to compare them, and to design new systems.
