Gap Preserving Reductions Between Reconfiguration Problems

Author Naoto Ohsaka

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Naoto Ohsaka
  • CyberAgent, Inc., Tokyo, Japan


I wish to thank the anonymous referees for their suggestions which help improve the presentation of this paper.

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Naoto Ohsaka. Gap Preserving Reductions Between Reconfiguration Problems. In 40th International Symposium on Theoretical Aspects of Computer Science (STACS 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 254, pp. 49:1-49:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


Combinatorial reconfiguration is a growing research field studying problems on the transformability between a pair of solutions for a search problem. For example, in SAT Reconfiguration, for a Boolean formula φ and two satisfying truth assignments σ_𝗌 and σ_𝗍 for φ, we are asked to determine whether there is a sequence of satisfying truth assignments for φ starting from σ_𝗌 and ending with σ_𝗍, each resulting from the previous one by flipping a single variable assignment. We consider the approximability of optimization variants of reconfiguration problems; e.g., Maxmin SAT Reconfiguration requires to maximize the minimum fraction of satisfied clauses of φ during transformation from σ_𝗌 to σ_𝗍. Solving such optimization variants approximately, we may be able to obtain a reasonable reconfiguration sequence comprising almost-satisfying truth assignments. In this study, we prove a series of gap-preserving reductions to give evidence that a host of reconfiguration problems are PSPACE-hard to approximate, under some plausible assumption. Our starting point is a new working hypothesis called the Reconfiguration Inapproximability Hypothesis (RIH), which asserts that a gap version of Maxmin CSP Reconfiguration is PSPACE-hard. This hypothesis may be thought of as a reconfiguration analogue of the PCP theorem. Our main result is PSPACE-hardness of approximating Maxmin 3-SAT Reconfiguration of bounded occurrence under RIH. The crux of its proof is a gap-preserving reduction from Maxmin Binary CSP Reconfiguration to itself of bounded degree. Because a simple application of the degree reduction technique using expander graphs due to Papadimitriou and Yannakakis (J. Comput. Syst. Sci., 1991) does not preserve the perfect completeness, we modify the alphabet as if each vertex could take a pair of values simultaneously. To accomplish the soundness requirement, we further apply an explicit family of near-Ramanujan graphs and the expander mixing lemma. As an application of the main result, we demonstrate that under RIH, optimization variants of popular reconfiguration problems are PSPACE-hard to approximate, including Nondeterministic Constraint Logic due to Hearn and Demaine (Theor. Comput. Sci., 2005), Independent Set Reconfiguration, Clique Reconfiguration, and Vertex Cover Reconfiguration.

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ACM Subject Classification
  • Theory of computation → Problems, reductions and completeness
  • combinatorial reconfiguration
  • hardness of approximation
  • gap reduction


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