On the Computation of Paracoherent Answer Sets

Giovanni Amendola, Carmine Dorado, Wolfgang Faber, Nicola Leone, Francesco Ricca

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

16 Citations (Scopus)


Answer Set Programming (ASP) is a well-established formalism for nonmonotonic reasoning. An ASP program can have no answer set due to cyclic default negation. In this case, it is not possible to draw any conclusion, even if this is not intended. Recently, several paracoherent semantics have been proposed that address this issue,and several potential applications for these semantics have been identified. However, paracoherent semantics have essentially been inapplicable in practice, due to the lack of efficient algorithms and implementations. In this paper, this lack is addressed, and several different algorithms to compute semi-stable and semi-equilibrium models are proposed and implemented into an answer set solving framework. An empirical performance comparison among the new algorithms on benchmarks from ASP competitions is given as well.
Original languageEnglish
Title of host publicationProceedings of the Thirty-First AAAI Conference on Artificial Intelligence
Subtitle of host publication(AAAAI-17)
EditorsSatinder Singh, Shaul Markovitch
PublisherAAAI press
Number of pages7
ISBN (Print)1577357809, 9781577357803
Publication statusPublished - 1 Jul 2017
Event31st Association for the Advancement of Artificial Intelligence Conference on Artificial Intelligence - Hilton San Francisco Union Square, San Francisco, United States
Duration: 4 Feb 20179 Feb 2017
Conference number: 31
https://aaai.org/ocs/index.php/AAAI/AAAI17/index (Link to Conference Details)


Conference31st Association for the Advancement of Artificial Intelligence Conference on Artificial Intelligence
Abbreviated titleAAAI-17
Country/TerritoryUnited States
CitySan Francisco
Internet address


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