ALPSolver: A Solver for Assumable Logic Programming

Assumable Logic Programming (ALP), an extension of Answer Set Programming (ASP), has been theoretically demonstrated to possess significant advantages in addressing problems involving incomplete information. Therefore, the development of ALP solvers is urgently needed to facilitate further research and applications. This paper proposes a solving algorithm named Answer Set Based View Search (ASBVS) and its optimization to compute the results of ALP programs. Based on this, the ALPSolver has been implemented and integrated into an online platform for public use. This paper experimentally validates the correctness of the solving algorithm and confirms the advantages of ALP in handling default information, indirect exception and abductive reasoning. Additionally, the experimental results demonstrate the effectiveness of the optimization algorithm, with a notable increase in efficiency as the problem scale increases.

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Published
2024-09-27
DOI
https://doi.org/10.1109/ichci63580.2024.10808015
Primary Topic
Formal Methods in Verification
Type
article
Field-Weighted Citation Impact
0.00

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article

ALPSolver: A Solver for Assumable Logic Programming

Haijun Tian, Jiayi Chen, Zhizheng Zhang
Formal Methods in Verification
article

ALPSolver: A Solver for Assumable Logic Programming

Haijun Tian, Jiayi Chen, Zhizheng Zhang
article en

Abstract

Assumable Logic Programming (ALP), an extension of Answer Set Programming (ASP), has been theoretically demonstrated to possess significant advantages in addressing problems involving incomplete information. Therefore, the development of ALP solvers is urgently needed to facilitate further research and applications. This paper proposes a solving algorithm named Answer Set Based View Search (ASBVS) and its optimization to compute the results of ALP programs. Based on this, the ALPSolver has been implemented and integrated into an online platform for public use. This paper experimentally validates the correctness of the solving algorithm and confirms the advantages of ALP in handling default information, indirect exception and abductive reasoning. Additionally, the experimental results demonstrate the effectiveness of the optimization algorithm, with a notable increase in efficiency as the problem scale increases.

Southeast University (CN)
Science and Technology Project of State Grid
Openalex Percentile: Top 71%
Formal Methods in Verification
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