Abstract

AbstractIn 2004 Atserias, Kolaitis, and Vardi proposed $\text {OBDD}$ -based propositional proof systems that prove unsatisfiability of a CNF formula by deduction of an identically false $\text {OBDD}$ from $\text {OBDD}$ s representing clauses of the initial formula. All $\text {OBDD}$ s in such proofs have the same order of variables. We initiate the study of $\text {OBDD}$ based proof systems that additionally contain a rule that allows changing the order in $\text {OBDD}$ s. At first we consider a proof system $\text {OBDD}(\land , \text{reordering})$ that uses the conjunction (join) rule and the rule that allows changing the order. We exponentially separate this proof system from $\text {OBDD}(\land )$ proof system that uses only the conjunction rule. We prove exponential lower bounds on the size of $\text {OBDD}(\land , \text{reordering})$ refutations of Tseitin formulas and the pigeonhole principle. The first lower bound was previously unknown even for $\text {OBDD}(\land )$ proofs and the second one extends the result of Tveretina et al. from $\text {OBDD}(\land )$ to $\text {OBDD}(\land , \text{reordering})$ .In 2001 Aguirre and Vardi proposed an approach to the propositional satisfiability problem based on $\text {OBDD}$ s and symbolic quantifier elimination (we denote algorithms based on this approach as $\text {OBDD}(\land , \exists )$ algorithms). We augment these algorithms with the operation of reordering of variables and call the new scheme $\text {OBDD}(\land , \exists , \text{reordering})$ algorithms. We notice that there exists an $\text {OBDD}(\land , \exists )$ algorithm that solves satisfiable and unsatisfiable Tseitin formulas in polynomial time (a standard example of a hard system of linear equations over $\mathbb {F}_2$ ), but we show that there are formulas representing systems of linear equations over $\mathbb {F}_2$ that are hard for $\text {OBDD}(\land , \exists , \text{reordering})$ algorithms. Our hard instances are satisfiable formulas representing systems of linear equations over $\mathbb {F}_2$ that correspond to checksum matrices of error correcting codes.

Highlights

  • An ordered binary decision diagram (OBDD) is a way to represent Boolean functions [3]

  • The second aim is to show that reordering of the variables is really useful; we give examples of formulas that are hard for the OBDD-based proof systems without reordering and easy with reordering

  • We prove two exponential lower bounds for the size of a OBDD(∧, reordering)-derivation of the pigeonhole principle PHPnn+1 and Tseitin formulas based on constant-degree algebraic expanders

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Summary

Introduction

An ordered binary decision diagram (OBDD) is a way to represent Boolean functions [3]. For some order of variables π we represent clauses of the input formula as a π-ordered BDD; we may derive a new OBDD applying either the conjunction rule or the weakening rule. The OBDD(∧, weakening)-proof system simulates Cutting Plane with unary coefficients and it is stronger than Resolution This proof system provides short refutations for the formulas that represent unsatisfiable systems of linear equations over F2 [1], while linear systems are hard for Resolution. An interesting approach to solving propositional satisfiability was suggested by Pan and Vardi [15] They proposed an algorithm that chooses some order π on the variables of the input CNF formula F and creates the current π-ordered BDD D that initially represents the constant true function, and a set of clauses S that initially consists of all clauses of the formula F. The result of [4] implies that an OBDD(∧, ∃)-algorithm can solve PHPnn+1 in polynomial time in compare to OBDD(∧)-algorithms and DPLL based algorithms

Statement of the problem
Our results
Ordered binary decision diagrams
OBDD-proofs
OBDD-algorithms for SAT
Error-correcting codes
Tseitin formulas
Pigeonhole principle
Code construction
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