research-article

Applying incremental answer set solving to product configuration

Authors:

Richard Comploi-Taupe,

Giulia Francescutto,

Gottfried SchennerAuthors Info & Claims

SPLC '22: Proceedings of the 26th ACM International Systems and Software Product Line Conference - Volume B

Pages 150 - 155

https://doi.org/10.1145/3503229.3547069

Published: 12 September 2022 Publication History

Abstract

In this paper, we apply incremental answer set solving to product configuration. Incremental answer set solving is a step-wise incremental approach to Answer Set Programming (ASP). We demonstrate how to use this technique to solve product configurations problems incrementally. Every step of the incremental solving process corresponds to a predefined configuration action. Using complex domain-specific configuration actions makes it possible to tightly control the level of non-determinism and performance of the solving process. We show applications of this technique for reasoning about product configuration, like simulating the behavior of a deterministic configuration algorithm and describing user actions.

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Cited By

Ebdelrehime EYounes AElkabani I(2024)Quantum Answer Set Programming Solver Using Amplitude Amplification2024 International Conference on Machine Intelligence and Smart Innovation (ICMISI)10.1109/ICMISI61517.2024.10580520(168-173)Online publication date: 12-May-2024
https://doi.org/10.1109/ICMISI61517.2024.10580520
Eiter TGeibinger TOetsch J(2023)Contrastive Explanations for Answer-Set ProgramsLogics in Artificial Intelligence10.1007/978-3-031-43619-2_6(73-89)Online publication date: 20-Sep-2023
https://dl.acm.org/doi/10.1007/978-3-031-43619-2_6

Index Terms

Applying incremental answer set solving to product configuration
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
      1. Logic programming and answer set programming

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Published In

cover image ACM Conferences

SPLC '22: Proceedings of the 26th ACM International Systems and Software Product Line Conference - Volume B

September 2022

246 pages

ISBN:9781450392068

DOI:10.1145/3503229

General Chairs:
Alexander Felfernig
Graz University of Technology, Austria
,
Lidia Fuentes
University of Málaga, Spain

Copyright © 2022 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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New York, NY, United States

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Published: 12 September 2022

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SPLC '22

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SIGSOFT

SPLC '22: 26th ACM International Systems and Software Product Line Conference

September 12 - 16, 2022

Graz, Austria

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SPLC '22 Paper Acceptance Rate 14 of 41 submissions, 34%;

Overall Acceptance Rate 167 of 463 submissions, 36%

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Cited By

Ebdelrehime EYounes AElkabani I(2024)Quantum Answer Set Programming Solver Using Amplitude Amplification2024 International Conference on Machine Intelligence and Smart Innovation (ICMISI)10.1109/ICMISI61517.2024.10580520(168-173)Online publication date: 12-May-2024
https://doi.org/10.1109/ICMISI61517.2024.10580520
Eiter TGeibinger TOetsch J(2023)Contrastive Explanations for Answer-Set ProgramsLogics in Artificial Intelligence10.1007/978-3-031-43619-2_6(73-89)Online publication date: 20-Sep-2023
https://dl.acm.org/doi/10.1007/978-3-031-43619-2_6

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