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ASP-Core-2 Input Language Format

Published online by Cambridge University Press:  20 December 2019

FRANCESCO CALIMERI Open the ORCID record for FRANCESCO CALIMERI [Opens in a new window] ,
WOLFGANG FABER ,
MARTIN GEBSER Open the ORCID record for MARTIN GEBSER [Opens in a new window] ,
GIOVAMBATTISTA IANNI ,
ROLAND KAMINSKI Open the ORCID record for ROLAND KAMINSKI [Opens in a new window] ,
THOMAS KRENNWALLNER ,
NICOLA LEONE ,
MARCO MARATEA ,
FRANCESCO RICCA Open the ORCID record for FRANCESCO RICCA [Opens in a new window]  and
TORSTEN SCHAUB Open the ORCID record for TORSTEN SCHAUB [Opens in a new window]
FRANCESCO CALIMERI
Affiliation:
DeMaCS, Università della Calabria, Rende, Italy (e-mail: [email protected])
WOLFGANG FABER
Affiliation:
Institut für Angewandte Informatik, Alpen-Adria-Universität, Klagenfurt, Austria (e-mails: [email protected], [email protected])
MARTIN GEBSER
Affiliation:
Institut für Angewandte Informatik, Alpen-Adria-Universität, Klagenfurt, Austria (e-mails: [email protected], [email protected])
GIOVAMBATTISTA IANNI
Affiliation:
DeMaCS, Università della Calabria, Rende, Italy (e-mail: [email protected])
ROLAND KAMINSKI
Affiliation:
Institute of Computer Science, University of Potsdam, Potsdam, Germany (e-mail: [email protected])
THOMAS KRENNWALLNER
Affiliation:
XIMES GmbH, Vienna, Austria (e-mail: [email protected])
NICOLA LEONE
Affiliation:
DeMaCS, Università della Calabria, Rende, Italy (e-mail: [email protected])
MARCO MARATEA
Affiliation:
DIBRIS, University of Genova, Genova, Italy (email: [email protected])
FRANCESCO RICCA
Affiliation:
DeMaCS, Università della Calabria, Rende, Italy (e-mail: [email protected])
TORSTEN SCHAUB
Affiliation:
Institute of Computer Science, University of Potsdam, Potsdam, Germany (e-mail: [email protected])
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Abstract

Standardization of solver input languages has been a main driver for the growth of several areas within knowledge representation and reasoning, fostering the exploitation in actual applications. In this document, we present the ASP-CORE-2 standard input language for Answer Set Programming, which has been adopted in ASP Competition events since 2013.

Keywords

Answer Set Programmingstandard languageknowledge representation and reasoningstandardization
Type
Original Article
Information
Theory and Practice of Logic Programming , Volume 20 , Issue 2 , March 2020 , pp. 294 - 309
Copyright
© Cambridge University Press 2019 

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References

Abiteboul, S., Hull, R. and Vianu, V. 1995. Foundations of Databases. Addison-Wesley.Google Scholar
Alviano, M., Calimeri, F., Faber, W., Leone, N. and Perri, S. 2011. Unfounded sets and well-founded semantics of answer set programs with aggregates. Journal of Artificial Intelligence Research 42, 487–527.Google Scholar
Alviano, M., Faber, W. and Gebser, M. 2015. Rewriting recursive aggregates in answer set programming: Back to monotonicity. Theory and Practice of Logic Programming 15, 4–5, 559–573.CrossRefGoogle Scholar
Brain, M., Faber, W., Maratea, M., Polleres, A., Schaub, T. and Schindlauer, R. 2007. What should an asp solver output? A multiple position paper. In Proceedings of the First International SEA’07 Workshop. CEUR Workshop Proceedings, vol. 281.Google Scholar
Brewka, G., Eiter, T. and Truszczyński, M. 2011. Answer set programming at a glance. Communications of the ACM 54, 12, 92–103.CrossRefGoogle Scholar
Calimeri, F., Cozza, S., Ianni, G. and Leone, N. 2011a. Finitely recursive programs: Decidability and bottom-up computation. AI Communications 24, 4, 311–334.CrossRefGoogle Scholar
Calimeri, F., Gebser, M., Maratea, M. and Ricca, F. 2016. Design and results of the Fifth Answer Set Programming Competition. Artificial Intelligence 231, 151–181.CrossRefGoogle Scholar
Calimeri, F., Ianni, G. and Ricca, F. 2014. The third open answer set programming competition. TPLP 14, 1, 117–135.Google Scholar
Calimeri, F., Ianni, G., Ricca, F. and della Calabria Organizing Committee, T. U. 2011b. Third ASP Competition, File and language formats. URL: http://www.mat.unical.it/aspcomp2011/files/LanguageSpecifications.pdf.Google Scholar
Dell’Armi, T., Faber, W., Ielpa, G., Leone, N. and Pfeifer, G. 2003. Aggregate functions in DLV. In Proceedings ASP03 - Answer Set Programming: Advances in Theory and Implementation, Messina, Italy, de Vos, M. and Provetti, A., Eds, 274–288. URL: http://CEUR-WS.org/Vol-78/.Google Scholar
Denecker, M., Pelov, N. and Bruynooghe, M. 2001. Ultimate well-founded and stable model semantics for logic programs with aggregates. In Proceedings of the 17th International Conference on Logic Programming, Codognet, P., Ed. Springer Verlag, 212–226.Google Scholar
Erdem, E., Gelfond, M. and Leone, N. 2016. Applications of answer set programming. AI Magazine 37, 3, 53–68.CrossRefGoogle Scholar
Faber, W., Leone, N. and Pfeifer, G. 2004. Recursive aggregates in disjunctive logic programs: Semantics and complexity. In Proceedings of the 9th European Conference on Artificial Intelligence (JELIA 2004), Alferes, J. J. and Leite, J., Eds. Lecture Notes in AI (LNAI), vol. 3229. Springer Verlag, 200–212.Google Scholar
Faber, W., Leone, N. and Pfeifer, G. 2011. Semantics and complexity of recursive aggregates in answer set programming. Artificial Intelligence 175, 1, 278–298. Special Issue: John McCarthy’s Legacy.CrossRefGoogle Scholar
Ferraris, P. 2005. Answer sets for propositional theories. In Logic Programming and Nonmonotonic Reasoning — 8th International Conference, LPNMR’05, Diamante, Italy, September 2005, Proceedings, Baral, C., Greco, G., Leone, N. and Terracina, G., Eds. Lecture Notes in Computer Science, vol. 3662. Springer Verlag, 119–131.Google Scholar
Gebser, M., Harrison, A., Kaminski, R., Lifschitz, V. and Schaub, T. 2015. Abstract Gringo. Theory and Practice of Logic Programming 15, 4–5, 449–463.CrossRefGoogle Scholar
Gebser, M., Kaminski, R., Kaufmann, B., Ostrowski, M., Schaub, T. and Wanko, P. 2016. Theory solving made easy with clingo 5. In Technical Communications of the 32nd International Conference on Logic Programming (ICLP 2016 TCs), Carro, M., King, A., Saeedloei, N. and Vos, M. D., Eds. OASICS, vol. 52. Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, 2:1–2:15.Google Scholar
Gebser, M., Leone, N., Maratea, M., Perri, S., Ricca, F. and Schaub, T. 2018a. Evaluation techniques and systems for answer set programming: A survey. In Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI 2018), Lang, J., Ed. ijcai.org, 5450–5456.Google Scholar
Gebser, M., Maratea, M. and Ricca, F. 2017a. The design of the seventh answer set programming competition. In Proceedings of the 14th International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR 2017), Balduccini, M. and Janhunen, T., Eds. Lecture Notes in Computer Science, vol. 10377. Springer, 3–9.Google Scholar
Gebser, M., Maratea, M. and Ricca, F. 2017b. The sixth answer set programming competition. Journal of Artificial Intelligence Research 60, 41–95.CrossRefGoogle Scholar
Gebser, M., Obermeier, P., Schaub, T., Ratsch-Heitmann, M. and Runge, M. 2018b. Routing driverless transport vehicles in car assembly with answer set programming. TPLP 18, 3–4, 520–534.Google Scholar
Gelfond, M. 2002. Representing knowledge in A-Prolog. In Computational Logic. Logic Programming and Beyond, Kakas, A. C. and Sadri, F., Eds. LNCS, vol. 2408. Springer, 413–451.Google Scholar
Gelfond, M. and Lifschitz, V. 1991. Classical negation in logic programs and disjunctive databases. New Generation Computing 9, 365–385.CrossRefGoogle Scholar
Gelfond, M. and Zhang, Y. 2014. Vicious circle principle and logic programs with aggregates. Theory and Practice of Logic Programming 14, 4–5, 587–601.CrossRefGoogle Scholar
Harrison, A. and Lifschitz, V. 2018. Relating two dialects of answer set programming. In Proceedings of the 17th International Workshop on Non-monotonic Reasoning (NMR 2018), Fermé, E. and Villata, S., Eds, 99–108.Google Scholar
Kemp, D. B. and Stuckey, P. J. 1991. Semantics of logic programs with aggregates. In Proceedings of the International Symposium on Logic Programming (ISLP’91), Saraswat, V. A. and Ueda, K., Eds. MIT Press, 387–401.Google Scholar
Krennwallner, T. 2013. ASP Competition, output format. URL: https://www.mat.unical.it/aspcomp2013/files/aspoutput.txt.Google Scholar
Leone, N. and Ricca, F. 2015. Answer set programming: A tour from the basics to advanced development tools and industrial applications. In Web Logic Rules - 11th International Summer School on Reasoning Web, Tutorial Lectures, Faber, W. and Paschke, A., Eds. Lecture Notes in Computer Science, vol. 9203. Springer, 308–326.Google Scholar
Lierler, Y., Maratea, M. and Ricca, F. 2016. Systems, engineering environments, and competitions. AI Magazine 37, 3, 45–52.CrossRefGoogle Scholar
Osorio, M. and Jayaraman, B. 1999. Aggregation and negation-as-failure. New Generation Computing 17, 3, 255–284.CrossRefGoogle Scholar
Pelov, N. 2004. Semantics of Logic Programs with Aggregates. Ph.D. thesis, Katholieke Universiteit Leuven, Leuven, Belgium.Google Scholar
Pelov, N., Denecker, M. and Bruynooghe, M. 2004. Partial stable models for logic programs with aggregates. In Proceedings of the 7th International Conference on Logic Programming and Non-Monotonic Reasoning (LPNMR-7). Lecture Notes in AI (LNAI), vol. 2923. Springer, 207–219.Google Scholar
Pelov, N., Denecker, M. and Bruynooghe, M. 2007. Well-founded and stable semantics of logic programs with aggregates. Theory and Practice of Logic Programming 7, 3, 301–353.CrossRefGoogle Scholar
Pelov, N. and Truszczyński, M. 2004. Semantics of disjunctive programs with monotone aggregates - An operator-based approach. In Proceedings of the 10th International Workshop on Non-monotonic Reasoning (NMR 2004), Whistler, BC, Canada, 327–334.Google Scholar
Ross, K. A. and Sagiv, Y. 1997. Monotonic aggregation in deductive databases. Journal of Computer and System Sciences 54, 1, 79–97.CrossRefGoogle Scholar
Simons, P., Niemelä, I. and Soininen, T. 2002. Extending and implementing the stable model semantics. Artificial Intelligence 138, 181–234.CrossRefGoogle Scholar
Van Gelder, A. 1992. The well-founded semantics of aggregation. In Proceedings of the Eleventh Symposium on Principles of Database Systems (PODS’92). ACM Press, 127–138.Google Scholar