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Random walks for selected boolean implication and equivalence problems

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Abstract

This paper is concerned with the design and analysis of a random walk algorithm for the 2CNF implication problem (2CNFI). In 2CNFI, we are given two 2CNF formulas \({\phi_{1}}\) and \({\phi_{2}}\) and the goal is to determine whether every assignment that satisfies \({\phi_{1}}\) , also satisfies \({\phi_{2}}\) . The implication problem is clearly coNP-complete for instances of kCNF, k ≥ 3; however, it can be solved in polynomial time, when k ≤ 2. The goal of this paper is to provide a Monte Carlo algorithm for 2CNFI with a bounded probability of error. The technique developed for 2CNFI is then extended to derive a randomized, polynomial time algorithm for the problem of checking whether a given 2CNF formula Nae-implies another 2CNF formula.

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Authors and Affiliations

  1. LDCSEE, West Virginia University, Morgantown, WV, USA

    K. Subramani

  2. Department of Mathematics, West Virginia University, Morgantown, WV, USA

    Hong-Jian Lai & Xiaofeng Gu

Authors
  1. K. Subramani
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  2. Hong-Jian Lai
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  3. Xiaofeng Gu
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Correspondence to K. Subramani.

Additional information

This research has been supported in part by the Air Force Office of Scientific Research under grant FA9550-06-1-0050.

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Subramani, K., Lai, HJ. & Gu, X. Random walks for selected boolean implication and equivalence problems. Acta Informatica 46, 155–168 (2009). https://doi.org/10.1007/s00236-009-0089-4

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  • DOI: https://doi.org/10.1007/s00236-009-0089-4

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