Wasp

Wasp is an ASP solver handling disjunctive logic programs under the stable model semantics. Wasp implements techniques originally introduced for SAT solving combined with optimization methods that have been specifically designed for ASP computation, such as source pointers enhancing unfounded sets computation and efficient techniques for stable model checking.

Wasp takes as input logic programs in the gringo format and SAT/MaxSAT formulas in DIMACS format.

Compilation

In order to compile wasp boost (http://www.boost.org/) and g++-4.6 (or more recent) are required.

If all libraries have been installed just type:

make

and pray!

Other compiling options are also available:

• BUILD=stats enables the usage of statistics
• BUILD=estats enables more statistics (this may have deteriorate the performance)
• BUILD=trace enables the possibility to trace the internal behavior of wasp
• BUILD=debug compiles wasp for debugging
• SCRIPT=python enables python2.7 interface
• SCRIPT=python3 enables python3 interface (version of python <= 3.7)
• SCRIPT=python38 enables python3 interface (version of python >= 3.8)
• SCRIPT=perl enables perl interface
• SCRIPT=all enables python2.7 and perl interfaces

Usage

In order to use Wasp you need a grounder. You can use either gringo (http://potassco.sourceforge.net/) or i-dlv (https://github.com/DeMaCS-UNICAL/I-DLV/wiki).

If the grounder has been downloaded just type:

./gringo filename | ./wasp

or

./i-dlv filename | ./wasp

Publications

• M. Alviano, C. Dodaro, N. Leone, and Francesco Ricca: Advances in WASP. Proceedings of LPNMR (2015). Download Reference
• M. Alviano, C. Dodaro, J. Marques-Silva, and F. Ricca: Optimal Stable Model Search: Algorithms and Implementation. Journal of Logic and Computation (In Press 2015). Download Reference
• M. Alviano, C. Dodaro, and Francesco Ricca: Anytime Computation of Cautious Consequences in Answer Set Programming. Theory and Practice of Logic Programming (2014). Download Reference
• M. Alviano, C. Dodaro, W. Faber, N. Leone, and Francesco Ricca: WASP: A Native ASP Solver Based on Constraint Learning. Proceedings of LPNMR (2013). Download Reference
• M. Alviano, C. Dodaro, and Francesco Ricca: Comparing Alternative Solutions for Unfounded Set Propagation in ASP. Proceedings of AI*IA (2013). Download Reference

Documentation

Team

• Mario Alviano, University of Calabria
• Carmine Dodaro, University of Calabria (main developer)
• Francesco Ricca, University of Calabria