IASCAR: Incremental Answer Set Counting by Anytime Refinement
Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review
Contributors
Abstract
Answer set programming (ASP) is a popular declarative programming paradigm with various applications. Programs can easily have so many answer sets that they cannot be enumerated in practice, but counting still allows to quantify solution spaces. If one counts under assumptions on literals, one obtains a tool to comprehend parts of the solution space, so called answer set navigation. But navigating through parts of the solution space requires counting many times, which is expensive in theory. There, knowledge compilation compiles instances into representations on which counting works in polynomial time. However, these techniques exist only for CNF formulas and compiling ASP programs into CNF formulas can introduce an exponential overhead. In this paper, we introduce a technique to iteratively count answer sets under assumptions on knowledge compilations of CNFs that encode supported models. Our anytime technique uses the principle of inclusion-exclusion to systematically improve bounds by over- and undercounting. In a preliminary empirical analysis we demonstrate promising results. After compiling the input (offline phase) our approach quickly (re)counts.
Details
Original language | English |
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Title of host publication | Logic Programming and Nonmonotonic Reasoning |
Editors | Georg Gottlob, Daniela Inclezan, Marco Maratea |
Publisher | Springer |
Pages | 217-230 |
Number of pages | 14 |
ISBN (electronic) | 978-3-031-15707-3 |
ISBN (print) | 978-3-031-15706-6 |
Publication status | Published - 2022 |
Peer-reviewed | Yes |
Publication series
Series | Lecture Notes in Computer Science |
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Volume | 13416 |
ISSN | 0302-9743 |
External IDs
Scopus | 85137979484 |
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Mendeley | e5cf7a9c-6164-3377-a40e-6dc361b99796 |
Keywords
ASJC Scopus subject areas
Keywords
- ASP, Answer set counting, Knowledge compilation