Enhancing Lazy Grounding with Lazy Normalization in Answer-Set Programming

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussavertaisarvioitu

Tutkijat

Organisaatiot

  • Vienna University of Technology

Kuvaus

Answer-Set Programming (ASP) is an expressive rule-based knowledge-representation formalism. Lazy grounding is a solving technique that avoids the well-known grounding bottleneck of traditional ASP evaluation but is restricted to normal rules, severely limiting its expressive power. In this work, we introduce a framework to handle aggregates by normalizing them on demand during lazy grounding, hence relieving the restrictions of lazy grounding significantly. We term our approach as lazy normalization and demonstrate its feasibility for different types of aggregates. Asymptotic behavior is analyzed and correctness of the presented lazy normalizations is shown. Benchmark results indicate that lazy normalization can bring up-to exponential gains in space and time as well as enable ASP to be used in new application areas.

Yksityiskohdat

AlkuperäiskieliEnglanti
OtsikkoProceedings of the 33rd AAAI Conference on Artificial Intelligence
TilaJulkaistu - 2019
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaAAAI Conference on Artificial Intelligence - Honolulu, Yhdysvallat
Kesto: 27 tammikuuta 20191 helmikuuta 2019
Konferenssinumero: 33
https://aaai.org/Conferences/AAAI-19/

Julkaisusarja

NimiProceedings of the AAAI Conference on Artificial Intelligence
KustantajaAAAI Press
Vuosikerta33
ISSN (painettu)2159-5399
ISSN (elektroninen)2374-3468

Conference

ConferenceAAAI Conference on Artificial Intelligence
LyhennettäAAAI
MaaYhdysvallat
KaupunkiHonolulu
Ajanjakso27/01/201901/02/2019
www-osoite

ID: 29616742