Generalizing Level Ranking Constraints for Monotone and Convex Aggregates
Janhunen, Tomi (2023-09)
Janhunen, Tomi
Teoksen toimittaja(t)
Costantini, Stefania
Pontelli, Enrico
Russo, Alessandra
Toni, Francesca
Calegari, Roberta
D'Avila Garcez, Artur
Dodaro, Carmina
Fabiano, Francesco
Gaggl, Sarah
Mileo, Alessandra
Open Publishing Association
09 / 2023
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-2023112810306
https://urn.fi/URN:NBN:fi:tuni-2023112810306
Kuvaus
Peer reviewed
Tiivistelmä
In answer set programming (ASP), answer sets capture solutions to search problems of interest and thus the efficient computation of answer sets is of utmost importance. One viable implementation strategy is provided by translation-based ASP where logic programs are translated into other KR formalisms such as Boolean satisfiability (SAT), SAT modulo theories (SMT), and mixed-integer programming (MIP). Consequently, existing solvers can be harnessed for the computation of answer sets. Many of the existing translations rely on program completion and level rankings to capture the minimality of answer sets and default negation properly. In this work, we take level ranking constraints into reconsideration, aiming at their generalizations to cover aggregate-based extensions of ASP in more systematic way. By applying a number of program transformations, ranking constraints can be rewritten in a general form that preserves the structure of monotone and convex aggregates and thus offers a uniform basis for their incorporation into translation-based ASP. The results open up new possibilities for the implementation of translators and solver pipelines in practice.
Kokoelmat
- TUNICRIS-julkaisut [19293]