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  • 标题:Quasipolynomial Normalisation in Deep Inference via Atomic Flows and Threshold Formulae
  • 本地全文:下载
  • 作者:Paola Bruscoli ; Alessio Guglielmi ; Tom Gundersen
  • 期刊名称:Logical Methods in Computer Science
  • 印刷版ISSN:1860-5974
  • 电子版ISSN:1860-5974
  • 出版年度:2016
  • 卷号:12
  • 期号:2
  • 页码:1
  • DOI:10.2168/LMCS-12(2:5)2016
  • 出版社:Technical University of Braunschweig
  • 摘要:Je\v{r}ábek showed that cuts in classical propositional logic proofs in deep inference can be eliminated in quasipolynomial time. The proof is indirect and it relies on a result of Atserias, Galesi and Pudlák about monotone sequent calculus and a correspondence between that system and cut-free deep-inference proofs. In this paper we give a direct proof of Je\v{r}ábek's result: we give a quasipolynomial-time cut-elimination procedure for classical propositional logic in deep inference. The main new ingredient is the use of a computational trace of deep-inference proofs called atomic flows, which are both very simple (they only trace structural rules and forget logical rules) and strong enough to faithfully represent the cut-elimination procedure.
  • 其他关键词:Proof theory, proof complexity, deep inference, threshold functions
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