Clasp

Answer set solver for (extended) normal logic programs

Clasp is an answer set solver for extended normal logic programs. It combines the high-level modeling capacities of answer set programming ASP with state-of-the-art techniques from the area of Boolean constraint solving. The primary clasp algorithm relies on conflict-driven nogood learning, a technique that proved very successful for satisfiability checking SAT. Unlike other learning ASP solvers, clasp does not rely on legacy software, such as a SAT solver or any other existing ASP solver. Rather, clasp has been genuinely developed for answer set solving based on conflict-driven nogood learning. clasp can be applied as an ASP solver on SMODELS format, as output by Gringo, as a SAT solver on a simplified version of DIMACS/CNF format, or as a PB solver on OPB format.