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BliStr: The Blind Strategymaker

8 pagesPublished: December 18, 2015


BliStr is a system that automatically develops strong targetted theorem-proving strategies for the E prover on a large set of diverse problems. The main idea is to interleave (i) iterated low-timelimit local search for new strategies on small sets of similar easy problems with (ii) higher-timelimit evaluation of the new strategies on all problems. The accumulated results of the global higher-timelimit runs are used to define and evolve the notion of "similar easy problems'", and to control the evolution of the next strategy. The technique significantly strengthened the set of E strategies used by the MaLARea, E-MaLeS, and E systems in the CASC@Turing 2012 competition, particularly in the Mizar division. Similar improvement was obtained on the problems created from the Flyspeck corpus.

Keyphrases: Artificial Intelligence, automated theorem proving, large-theory automated reasoning, strategy development

In: Georg Gottlob, Geoff Sutcliffe and Andrei Voronkov (editors). GCAI 2015. Global Conference on Artificial Intelligence, vol 36, pages 312--319

BibTeX entry
  author    = {Josef Urban},
  title     = {BliStr: The Blind Strategymaker},
  booktitle = {GCAI 2015. Global Conference on Artificial Intelligence},
  editor    = {Georg Gottlob and Geoff Sutcliffe and Andrei Voronkov},
  series    = {EPiC Series in Computing},
  volume    = {36},
  pages     = {312--319},
  year      = {2015},
  publisher = {EasyChair},
  bibsource = {EasyChair,},
  issn      = {2398-7340},
  url       = {},
  doi       = {10.29007/8n7m}}
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