An Efficient Algorithm for Semi-stable Extensions

Federico Cerutti, Massimiliano Giacomin, Mauro Vallati, Tobia Zanetti

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


In this paper we introduce AASExts, an algorithm for computing semi–stable extensions. We improve techniques developed for other semantics, notably preferred semantics, as well as leverage recent advances in All-SAT community. We prove our proposed algorithm is sound and complete, we describe the experiments to select the most appropriate encoding to adopt, and we show empirically that our implementation significantly outperforms even sophisticated ASP-based and SAT-based reduction approaches on existing benchmarks.

Original languageEnglish
Title of host publicationAIxIA 2020 – Advances in Artificial Intelligence
Subtitle of host publicationXIXth International Conference of the Italian Association for Artificial Intelligence, Revised Selected Papers
EditorsMatteo Baldoni, Stefania Bandini
Place of PublicationCham
PublisherSpringer Nature Switzerland AG
Number of pages19
VolumeLNCS/LNAI 12414
ISBN (Electronic)9783030770914
ISBN (Print)9783030770907
Publication statusPublished - 22 May 2021
Event19th International Conference of the Italian Association for Artificial Intelligence - Virtual, Online
Duration: 24 Nov 202027 Nov 2020
Conference number: 19

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Nature Switzerland AG
Volume12414 LNAI/LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference19th International Conference of the Italian Association for Artificial Intelligence
Abbreviated titleAIxIA 2020
CityVirtual, Online


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