Artificial Neural Networks and Machine Learning – ICANN 2012

Volume 7553 of the series Lecture Notes in Computer Science pp 427-434

Neural Networks for Proof-Pattern Recognition

  • Ekaterina KomendantskayaAffiliated withSchool of Computing, University of Dundee
  • , Kacper LichotaAffiliated withSchool of Computing, University of Dundee

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We propose a new method of feature extraction that allows to apply pattern-recognition abilities of neural networks to data-mine automated proofs. We propose a new algorithm to represent proofs for first-order logic programs as feature vectors; and present its implementation. We test the method on a number of problems and implementation scenarios, using three-layer neural nets with backpropagation learning.


Machine learning pattern-recognition data mining neural networks first-order logic programs automated proofs