Article

Recongo: Bounded Combinatorial Reconfiguration with Answer Set Programming

Authors:

Mutsunori Banbara,

Torsten SchaubAuthors Info & Claims

Logics in Artificial Intelligence: 18th European Conference, JELIA 2023, Dresden, Germany, September 20–22, 2023, Proceedings

Pages 278 - 286

https://doi.org/10.1007/978-3-031-43619-2_20

Published: 24 September 2023 Publication History

Abstract

We develop an approach called bounded combinatorial reconfiguration for solving combinatorial reconfiguration problems based on Answer Set Programming. The general task is to study the solution spaces of source combinatorial problems and to decide whether or not there are sequences of feasible solutions that have special properties. The resulting recongo solver covers all metrics of the solver track in the most recent international competition on combinatorial reconfiguration (CoRe Challenge 2022). recongo ranked first in the shortest metric of the single-engine solvers track.

References

[1]

Baral, C.: Knowledge Representation, Reasoning and Declarative Problem Solving. Cambridge University Press, Cambridge (2003)

[2]

Biere, A.: Bounded model checking. In: Handbook of Satisfiability, pp. 457–481. IOS Press, Amsterdam (2009)

[3]

Bonsma PS and Cereceda L Finding paths between graph colourings: PSPACE-completeness and superpolynomial distances Theor. Comput. Sci. 2009 410 50 5215-5226

[4]

Brewster RC, McGuinness S, Moore BR, and Noel JA A dichotomy theorem for circular colouring reconfiguration Theor. Comput. Sci. 2016 639 1-13

[5]

Cereceda L, van den Heuvel J, and Johnson M Finding paths between 3-colorings J. Graph Theory 2011 67 1 69-82

[6]

Gebser, M., et al.: Potassco User Guide. 2 edn. University of Potsdam (2015). http://potassco.org

[7]

Gebser M, Kaminski R, Kaufmann B, and Schaub T Answer Set Solving in Practice 2012 San Rafael Morgan and Claypool Publishers

[8]

Gelfond, M., Lifschitz, V.: The stable model semantics for logic programming. In: Kowalski, R., Bowen, K. (eds.) Proceedings of the Fifth International Conference and Symposium of Logic Programming (ICLP 1988), pp. 1070–1080. MIT Press (1988)

[9]

Gopalan P, Kolaitis PG, Maneva EN, and Papadimitriou CH The connectivity of Boolean satisfiability: Computational and structural dichotomies SIAM J. Comput. 2009 38 6 2330-2355

[10]

Haddadan A et al. The complexity of dominating set reconfiguration Theor. Comput. Sci. 2016 651 37-49

[11]

van den Heuvel, J.: The complexity of change. In: Blackburn, S.R., Gerke, S., Wildon, M. (eds.) Surveys in Combinatorics 2013, London Mathematical Society Lecture Note Series, vol. 409, pp. 127–160. Cambridge University Press (2013)

[12]

Ito T et al. On the complexity of reconfiguration problems Theor. Comput. Sci. 2011 412 12–14 1054-1065

[13]

Ito T, Kaminski M, and Demaine ED Reconfiguration of list edge-colorings in a graph Discrete Appl. Math. 2012 160 15 2199-2207

[14]

Ito T, Kamiński M, Ono H, Suzuki A, Uehara R, and Yamanaka K Gopal TV, Agrawal M, Li A, and Cooper SB On the parameterized complexity for token jumping on graphs Theory and Applications of Models of Computation 2014 Cham Springer 341-351

[15]

Ito T, Ono H, and Otachi Y Jain R, Jain S, and Stephan F Reconfiguration of cliques in a graph Theory and Applications of Models of Computation 2015 Cham Springer 212-223

[16]

Kaminski M, Medvedev P, and Milanic M Complexity of independent set reconfigurability problems Theor. Comput. Sci. 2012 439 9-15

[17]

Kaminski R, Romero J, Schaub T, and Wanko P How to build your own ASP-based system?! Theory Pract. Logic Program. 2023 23 1 299-361

[18]

Kautz, H.A., Selman, B.: Planning as satisfiability. In: Proceedings of the 10th European Conference on Artificial Intelligence (ECAI 1992), pp. 359–363 (1992)

[19]

Kautz, H.A., Selman, B.: Pushing the envelope: planning, propositional logic and stochastic search. In: Proceedings of the 13th National Conference on Artificial Intelligence (AAAI 1996), pp. 1194–1201 (1996)

[20]

Mouawad AE, Nishimura N, Pathak V, and Raman V Shortest reconfiguration paths in the solution space of Boolean formulas SIAM J. Discrete Math. 2017 31 3 2185-2200

[21]

Niemelä I Logic programs with stable model semantics as a constraint programming paradigm Ann. Math. Artif. Intell. 1999 25 3–4 241-273

[22]

Nishimura N Introduction to reconfiguration Algorithms 2018 11 4 52

[23]

Soh, T., Okamoto, Y., Ito, T.: Core challenge 2022: solver and graph descriptions. CoRR abs/2208.02495 (2022)

[24]

Suzuki A, Mouawad AE, and Nishimura N Reconfiguration of dominating sets J. Comb. Optim. 2016 32 4 1182-1195

[25]

Takaoka A Complexity of Hamiltonian cycle reconfiguration Algorithms 2018 11 9 140

[26]

Yamada, Y., Banbara, M., Inoue, K., Schaub, T.: Bounded combinatorial reconfiguration with answer set programming. CoRR abs/2307.10688 (2023)

[27]

Hirate T., et al.: Hamiltonian cycle reconfiguration with answer set programming. JELIA 2023. to appear

Cited By

Yamada YBanbara MInoue KSchaub TUehara R(2024)Combinatorial Reconfiguration with Answer Set Programming: Algorithms, Encodings, and Empirical AnalysisWALCOM: Algorithms and Computation10.1007/978-981-97-0566-5_18(242-256)Online publication date: 18-Mar-2024
https://dl.acm.org/doi/10.1007/978-981-97-0566-5_18

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Information

Published In

cover image Guide Proceedings

Logics in Artificial Intelligence: 18th European Conference, JELIA 2023, Dresden, Germany, September 20–22, 2023, Proceedings

Sep 2023

833 pages

ISBN:978-3-031-43618-5

DOI:10.1007/978-3-031-43619-2

Editors:
Sarah Gaggl
https://ror.org/042aqky30TU Dresden, Dresden, Germany
,
Maria Vanina Martinez
Artificial Intelligence Research Institute - IIIA CSIC, Barcelona, Spain
,
Magdalena Ortiz
https://ror.org/05kb8h459Umeå University, Umeå, Sweden

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 24 September 2023

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Cited By

Yamada YBanbara MInoue KSchaub TUehara R(2024)Combinatorial Reconfiguration with Answer Set Programming: Algorithms, Encodings, and Empirical AnalysisWALCOM: Algorithms and Computation10.1007/978-981-97-0566-5_18(242-256)Online publication date: 18-Mar-2024
https://dl.acm.org/doi/10.1007/978-981-97-0566-5_18

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