Answer Set Counting and its Applications

We have focused on Answer Set Programming (ASP), more specifically, answer set counting, exploring both exact and approximate methodologies. We developed an exact ASP counter, sharpASP, which utilizes a compact encoding for propositional formulas, significantly enhancing efficiency compared to existing methods that often struggle with inefficient encodings. Our evaluations indicate that sharpASP outperforms current ASP counters on several benchmarks. In addition, we proposed an approximate ASP counter, named ApproxASP, a hashing-based counter integrating Gauss-Jordan elimination within the ASP solver, clingo. As a practical application, we employed ApproxASP for network reliability estimation, demonstrating superior performance over both traditional reliability estimators and #SAT-based methods.

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Publication Details

Journal
Electronic Proceedings in Theoretical Computer Science
Published
2025-02-11
DOI
https://doi.org/10.4204/eptcs.416.34
Primary Topic
Bayesian Modeling and Causal Inference
Type
article
Field-Weighted Citation Impact
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article

Answer Set Counting and its Applications

Mohimenul Kabir
Electronic Proceedings in Theoretical Computer Science
Bayesian Modeling and Causal Inference
article

Answer Set Counting and its Applications

Mohimenul Kabir
article en

Abstract

We have focused on Answer Set Programming (ASP), more specifically, answer set counting, exploring both exact and approximate methodologies. We developed an exact ASP counter, sharpASP, which utilizes a compact encoding for propositional formulas, significantly enhancing efficiency compared to existing methods that often struggle with inefficient encodings. Our evaluations indicate that sharpASP outperforms current ASP counters on several benchmarks. In addition, we proposed an approximate ASP counter, named ApproxASP, a hashing-based counter integrating Gauss-Jordan elimination within the ASP solver, clingo. As a practical application, we employed ApproxASP for network reliability estimation, demonstrating superior performance over both traditional reliability estimators and #SAT-based methods.

Electronic Proceedings in Theoretical Computer ScienceVol. 416
National University of Singapore (SG)
Openalex Percentile: Top 99%
Bayesian Modeling and Causal Inference
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