MaLeCoP - Machine Learning Connection Prover

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F11%3A00191749" target="_blank" >RIV/68407700:21230/11:00191749 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

MaLeCoP - Machine Learning Connection Prover

Original language description

Probabilistic guidance based on learned knowledge is added to the connection tableau calculus and implemented on top of the lean-CoP theorem prover, linking it to an external advisor system. In the typical mathematical setting of solving many problems ina large complex theory, learning from successful solutions is then used for guiding theorem proving attempts in the spirit of the MaLARea system. While in MaLARea learning-based axiom selection is done outside unmodified theorem provers, in MaLeCoP thelearning-based selection is done inside the prover, and the interaction between learning of knowledge and its application can be much finer. This brings interesting possibilities for further construction and training of self-learning AI mathematical experts on large mathematical libraries, some of which are discussed. The initial implementation is evaluated on the MPTP Challenge large theory benchmark

Czech name

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Czech description

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Type

R - Software

CEP classification

JD - Use of computers, robotics and its application

OECD FORD branch

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Project

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Continuities

Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2011

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Internal product ID

MaLeCoP

Technical parameters

"open source", SWI-Prolog, UNIX-Bash, Perl

Economical parameters

Nemá ekonomické parametry, určeno pro základní výzkum v oboru automatického uvažování a strojového učení.

Owner IČO

68407700

Owner name

ČVUT FEL Katedra kybernetiky