Abstract
The Potsdam answer set solving collection, or Potassco for short, bundles various tools implementing and/or applying answer set programming. The article at hand succeeds an earlier description of the Potassco project published in Gebser et al. (AI Commun 24(2):107–124, 2011). Hence, we concentrate in what follows on the major features of the most recent, fifth generation of the ASP system clingo and highlight some recent resulting application systems.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Banbara M, Inoue K, Kaufmann B, Okimoto T, Schaub T, Soh T, Tamura N, Wanko P (2018) teaspoon: solving the curriculum-based course timetabling problems with answer set programming. Ann Oper Res (To appear)
Brewka G, Delgrande J, Romero J, Schaub T (2015) asprin: customizing answer set preferences without a headache. In: Bonet B, Koenig S (eds) Proceedings of the twenty-ninth national conference on artificial intelligence (AAAI’15). AAAI Press, pp 1467–1474 (2015). http://www.aaai.org/ocs/index.php/AAAI/AAAI15/paper/view/9535
Calimeri F, Faber W, Gebser M, Ianni G, Kaminski R, Krennwallner T, Leone N, Ricca F, Schaub T (2012) ASP-Core-2: Input language format. Available at https://www.mat.unical.it/aspcomp2013/ASPStandardization
Dimopoulos Y, Gebser M, Lühne P, Romero J, Schaub T (2017) plasp 3: towards effective ASP planning. In: Balduccini M, Janhunen T (eds) Proceedings of the fourteenth international conference on logic programming and nonmonotonic reasoning (LPNMR’17). Lecture Notes in Artificial Intelligence, vol. 10377, Springer, pp 286–300
Gebser M, Harrison A, Kaminski R, Lifschitz V, Schaub T (2015) Abstract Gringo. Theory Pract Log Program 15(4–5):449–463
Gebser M, Kaminski R, Kaufmann B, Ostrowski M, Schaub T, Schneider M (2011) Potassco: the potsdam answer set solving collection. AI Commun 24(2):107–124
Gebser M, Kaminski R, Kaufmann B, Schaub T (2012) Answer set solving in practice. Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan and Claypool Publishers, San Rafael
Gebser M, Kaminski R, Schaub T (2011) aspcud: a Linux package configuration tool based on answer set programming. In: Drescher C, Lynce I, Treinen R (eds) Proceedings of the second international workshop on logics for component configuration (LoCoCo’11), electronic proceedings in theoretical computer science (EPTCS), vol 65, pp 12–25
Janhunen T, Kaminski R, Ostrowski M, Schaub T, Schellhorn S, Wanko P (2017) Clingo goes linear constraints over reals and integers. Theory Prac Logic Program 17(5–6):872–888
Kaminski R, Schaub T, Wanko P (2017) A tutorial on hybrid answer set solving with clingo. In: Ianni G, Lembo D, Bertossi L, Faber W, Glimm B, Gottlob G, Staab S (eds) Proceedings of the thirteenth international summer school of the reasoning web. Lecture Notes in Computer Science, vol 10370, Springer, pp 167–203
Kaufmann B, Leone N, Perri S, Schaub T (2016) Grounding and solving in answer set programming. AI Mag 37(3):25–32
Newman N, Fréchette A, Leyton-Brown K (2018) Deep optimization for spectrum repacking. Commun ACM 61(1):97–104
Opolka S, Obermeier P, Schaub T (2015) Automatic genre-dependent composition using answer set programming. In: Proceedings of the twenty-first international symposium on electronic art (ISEA’15). http://isea2015.org/proceeding/submissions/ISEA2015_submission_78.pdf
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Gebser, M., Kaminski, R., Kaufmann, B. et al. The Potsdam Answer Set Solving Collection 5.0. Künstl Intell 32, 181–182 (2018). https://doi.org/10.1007/s13218-018-0528-x
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13218-018-0528-x