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Octopus: Combining Learning and Parallel Search

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Abstract

This paper presents Octopus, an automated theorem-proving system that combines learning and parallel search. The learning technique involves proving a simpler version of a given theorem and then using what it has learned to prove the given theorem. As of January 2004 Octopus had successfully proved 43 of the 1.0-rated theorems of the TPTP Problem Library.

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  1. School of Computer Science, McGill University, Canada

    Monty Newborn & Zongyan Wang

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  1. Monty Newborn
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  2. Zongyan Wang
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Correspondence to Monty Newborn.

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Newborn, M., Wang, Z. Octopus: Combining Learning and Parallel Search. J Autom Reasoning 33, 171–218 (2004). https://doi.org/10.1007/s10817-004-3243-2

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