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Machine Learner for Automated Reasoning 0.4 and 0.5

7 pagesPublished: July 5, 2015

Abstract

Machine Learner for Automated Reasoning (MaLARea) is a learning and
reasoning system for proving in large formal libraries where
thousands of theorems are available when attacking a new
conjecture, and a large number of related problems and proofs can be used to
learn specific theorem-proving knowledge. The last version of the
system has by a large margin won the 2013 CASC LTB competition. This
paper describes the motivation behind the methods used in MaLARea,
discusses the general approach and the issues arising in evaluation
of such system, and describes the Mizar@Turing100 and CASC'24
versions of MaLARea.

Keyphrases: ATP Competitions, automated reasoning, formal mathematics, large theories, machine learning

In: Stephan Schulz, Leonardo de Moura and Boris Konev (editors). PAAR-2014. 4th Workshop on Practical Aspects of Automated Reasoning, vol 31, pages 60--66

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