Paola Bruscoli ; Alessio Guglielmi ; Tom Gundersen ; Michel Parigot - Quasipolynomial Normalisation in Deep Inference via Atomic Flows and Threshold Formulae

lmcs:1637 - Logical Methods in Computer Science, May 3, 2016, Volume 12, Issue 2 - https://doi.org/10.2168/LMCS-12(2:5)2016
Quasipolynomial Normalisation in Deep Inference via Atomic Flows and Threshold FormulaeArticle

Authors: Paola Bruscoli ; Alessio Guglielmi ORCID; Tom Gundersen ; Michel Parigot

    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.


    Volume: Volume 12, Issue 2
    Published on: May 3, 2016
    Submitted on: April 29, 2014
    Keywords: Computer Science - Computational Complexity,Computer Science - Logic in Computer Science,F.4.1,F.2.2
    Funding:
      Source : OpenAIRE Graph
    • Complexity and Non-determinism in Deep Inference; Funder: UK Research and Innovation; Code: EP/E042805/1

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