Nearly-Exponential Size Lower Bounds for Symbolic Quantifier Elimination Algorithms and OBDD-Based Proofs of Unsatisfiability

Computer Science – Computational Complexity

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

40 pages, 3 figures. First public draft, comments welcome. Also submitted at ECCC

Scientific paper

We demonstrate a family of propositional formulas in conjunctive normal form so that a formula of size $N$ requires size $2^{\Omega(\sqrt[7]{N/logN})}$ to refute using the tree-like OBDD refutation system of Atserias, Kolaitis and Vardi with respect to all variable orderings. All known symbolic quantifier elimination algorithms for satisfiability generate tree-like proofs when run on unsatisfiable CNFs, so this lower bound applies to the run-times of these algorithms. Furthermore, the lower bound generalizes earlier results on OBDD-based proofs of unsatisfiability in that it applies for all variable orderings, it applies when the clauses are processed according to an arbitrary schedule, and it applies when variables are eliminated via quantification.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Nearly-Exponential Size Lower Bounds for Symbolic Quantifier Elimination Algorithms and OBDD-Based Proofs of Unsatisfiability does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Nearly-Exponential Size Lower Bounds for Symbolic Quantifier Elimination Algorithms and OBDD-Based Proofs of Unsatisfiability, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Nearly-Exponential Size Lower Bounds for Symbolic Quantifier Elimination Algorithms and OBDD-Based Proofs of Unsatisfiability will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-722866

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.