Open AccessModels set pre-processing for genetic programming based evolvement of models of models
Author(s) -
Mariia Semenkina,
Bogdan Burlacu,
Michael Affenzeller,
Erik Pitzer
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/734/1/012108
Subject(s) - computer science , genetic programming , set (abstract data type) , extension (predicate logic) , preprocessor , reuse , cluster analysis , genetic algorithm , data mining , theoretical computer science , artificial intelligence , mathematical optimization , machine learning , programming language , mathematics , engineering , waste management
We describe in this paper an extension of standard Genetic Programming where the terminal set of the algorithm is expanded with a set of basic models generated offline using a deterministic approach. The new algorithm called EMM-GP (Genetic Programming based Evolvement of Models of Models) uses a specialized mutation operator to sample this set during the recombination phase in order to create models that reuse valuable building blocks. In this work, a preprocessing of model set by means of clustering is considered.