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Encoding Hard String Problems with Answer Set Programming

Author Dominik Köppl

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Dominik Köppl
  • Department of Computer Science, Universität Münster, Germany

Funding

Supported by JSPS KAKENHI Grant Numbers JP21K17701 and JP23H04378.

Acknowledgements

We thank Mutsunori Banbara for drawing our attention to the ASP language.

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Dominik Köppl. Encoding Hard String Problems with Answer Set Programming. In 34th Annual Symposium on Combinatorial Pattern Matching (CPM 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 259, pp. 17:1-17:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023) https://doi.org/10.4230/LIPIcs.CPM.2023.17

Abstract

Despite the simple, one-dimensional nature of strings, several computationally hard problems on strings are known. Tackling hard problems beyond sizes of toy instances with straight-forward solutions is infeasible. To solve these problems on datasets of even small sizes, effort has to be put into the conception of algorithms leveraging profound characteristics of the input. Finding these characteristics can be eased by rapidly creating and evaluating prototypes of new concepts in how to tackle hard problems. Such a rapid-prototyping method for hard problems is answer set programming (ASP). In this light, we study the application of ASP on five NP-hard optimization problems in the field of strings. We provide MAX-SAT and ASP encodings, and empirically reason about the merits and flaws when working with ASP solvers.

Subject Classification

ACM Subject Classification
  • Theory of computation
  • Computing methodologies → Artificial intelligence
  • Theory of computation → Discrete optimization
  • Hardware → Theorem proving and SAT solving
Keywords
  • optimization problems
  • answer set programming
  • MAX-SAT encoding
  • NP-hard string problems

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Supplementary Materials

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