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  • 标题:QBF with Soft Variables
  • 本地全文:下载
  • 作者:Sven Reimer ; Matthias Sauer ; Paolo Marin
  • 期刊名称:Electronic Communications of the EASST
  • 电子版ISSN:1863-2122
  • 出版年度:2014
  • 卷号:70
  • 语种:English
  • 出版社:European Association of Software Science and Technology (EASST)
  • 摘要:QBF formulae are usually considered in prenex form, i.e. the quantifierblock is completely separated from the propositional part of the QBF.Among others, the semantics of the QBF is defined by the sequence ofthe variables within the prefix, where existentially quantifiedvariables depend on all universally quantified variables stated to theleft. In this paper we extend that classical definition and consider a newquantification type which we call soft variable. The idea is toallow a flexible position and quantifier type for these variables.Hence the type of quantifier of the soft variable can also bealtered. Based on this concept, we present an optimization problemseeking an optimal prefix as defined by user-given preferences. We statean algorithm based on MaxQBF, and present several applications – mainlyfrom verification area – which can be naturally translated into theoptimization problem for QBF with soft variables. We further implementeda prototype solver for this formalism, and compare our approach toprevious work, that differently from ours does not guarantee optimalityand completeness.
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