WASP: a native ASP solver based on constraint learning. This paper introduces WASP, an ASP solver handling disjunctive logic programs under the stable model semantics. WASP implements techniques originally introduced for SAT solving that have been extended to cope with ASP programs. Among them are restarts, conflict-driven constraint learning and backjumping. Moreover, WASP combines these SAT-based techniques with optimization methods that have been specifically designed for ASP computation, such as source pointers enhancing unfounded-sets computation, forward and backward inference operators based on atom support, and techniques for stable model checking. Concerning the branching heuristics, WASP adopts the BerkMin criterion hybridized with look-ahead techniques. The paper also reports on the results of experiments, in which WASP has been run on the system track of the third ASP Competition.

References in zbMATH (referenced in 36 articles , 1 standard article )

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  1. Amendola, Giovanni; Ricca, Francesco; Truszczynski, Miroslaw: New models for generating hard random Boolean formulas and disjunctive logic programs (2020)
  2. Alviano, Mario; Amendola, Giovanni; Dodaro, Carmine; Leone, Nicola; Maratea, Marco; Ricca, Francesco: Evaluation of disjunctive programs in WASP (2019)
  3. Alviano, Mario; Dodaro, Carmine; Fichte, Johannes K.; Hecher, Markus; Philipp, Tobias; Rath, Jakob: Inconsistency proofs for ASP: the ASP-DRUPE format (2019)
  4. Alviano, Mario; Faber, Wolfgang: Chain answer sets for logic programs with generalized atoms (2019)
  5. Alviano, Mario; Leone, Nicola; Veltri, Pierfrancesco; Zangari, Jessica: Enhancing magic sets with an application to ontological reasoning (2019)
  6. Amendola, Giovanni; Dodaro, Carmine; Maratea, Marco: Abstract solvers for computing cautious consequences of ASP programs (2019)
  7. Amendola, Giovanni; Dodaro, Carmine; Ricca, Francesco: Better paracoherent answer sets with less resources (2019)
  8. Amendola, Giovanni; Ricca, Francesco; Truszczynski, Miroslaw: Beyond NP: quantifying over answer sets (2019)
  9. Calimeri, Francesco; Ianni, Giovambattista; Pacenza, Francesco; Perri, Simona; Zangari, Jessica: Incremental answer set programming with overgrounding (2019)
  10. Cuteri, Bernardo; Dodaro, Carmine; Ricca, Francesco; Schüller, Peter: Partial compilation of ASP programs (2019)
  11. Dodaro, Carmine; Gasteiger, Philip; Reale, Kristian; Ricca, Francesco; Schekotihin, Konstantin: Debugging non-ground ASP programs: technique and graphical tools (2019)
  12. Ellmauthaler, Stefan (ed.); Schulz, Claudia (ed.): Introduction to the TPLP special issue on user-oriented logic programming and reasoning paradigms (2019)
  13. Fandinno, Jorge; Schulz, Claudia: Answering the “why” in answer set programming -- a survey of explanation approaches (2019)
  14. Gelfond, Michael; Zhang, Yuanlin: Vicious circle principle, aggregates, and formation of sets in ASP based languages (2019)
  15. Leone, Nicola; Allocca, Carlo; Alviano, Mario; Calimeri, Francesco; Civili, Cristina; Costabile, Roberta; Fiorentino, Alessio; Fuscà, Davide; Germano, Stefano; Laboccetta, Giovanni; Cuteri, Bernardo; Manna, Marco; Perri, Simona; Reale, Kristian; Ricca, Francesco; Veltri, Pierfrancesco; Zangari, Jessica: Enhancing DLV for large-scale reasoning (2019)
  16. Schüller, Peter: The Hexlite solver. Lightweight and efficient evaluation of HEX programs (2019)
  17. Alviano, Mario; Dodaro, Carmine; Järvisalo, Matti; Maratea, Marco; Previti, Alessandro: Cautious reasoning in ASP via minimal models and unsatisfiable cores (2018)
  18. Alviano, Mario; Dodaro, Carmine; Maratea, Marco: Shared aggregate sets in answer set programming (2018)
  19. Bliem, Bernhard: Treewidth in non-ground answer set solving and alliance problems in graphs (2018)
  20. Gebser, Martin; Kaminski, Roland; Kaufmann, Benjamin; Schaub, Torsten: Multi-shot ASP solving with clingo (2018)

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