MaLeCoP
swMATH ID:  7197 
Software Authors:  Josef Urban, Jiří Vyskočil, Petr Štěpánek 
Description:  MaLeCoP Machine Learning Connection Prover. Probabilistic guidance based on learned knowledge is added to the connection tableau calculus and implemented on top of the leanCoP theorem prover, linking it to an external advisor system. In the typical mathematical setting of solving many problems in a large complex theory, learning from successful solutions is then used for guiding theorem proving attempts in the spirit of the MaLARea system. While in MaLA Rea learningbased axiom selection is done outside unmodified theorem provers, in MaLeCoP the learningbased 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 selflearning AI mathematical experts on large mathematical libraries, some of which are discussed. The initial implementation is evaluated on the MPTP Challenge large theory benchmark 
Homepage:  http://rd.springer.com/chapter/10.1007%2F9783642221194_21 
Related Software:  E Theorem Prover; Mizar; MaLARea; VAMPIRE; FEMaLeCoP; Flyspeck; HOL Light; MPTP 0.2; leanCoP; ENIGMA; HOL; Isabelle/HOL; BliStr; Coq; TPTP; MoMM; ileanCoP; Isabelle; Sledgehammer; MPTP 
Cited in:  29 Publications 
Standard Articles
1 Publication describing the Software, including 1 Publication in zbMATH  Year 

MaLeCoP. Machine learning connection prover. Zbl 1332.68206 Urban, Josef; Vyskočil, Jiří; Štěpánek, Petr 
2011

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top 5
Cited by 36 Authors
Cited in 5 Serials
3  Journal of Automated Reasoning 
1  Journal of Symbolic Computation 
1  Annals of Mathematics and Artificial Intelligence 
1  Mathematics in Computer Science 
1  Journal of Formalized Reasoning 
Cited in 3 Fields
29  Computer science (68XX) 
3  Mathematical logic and foundations (03XX) 
1  Geometry (51XX) 