Open AccessEVOLUTIONAL METHODS FOR CREATING ARTIFICIAL INTELLIGENCE OF ROBOTIC TECHNICAL SYSTEMS
Author(s) -
Askhat Diveev,
S.I. Ibadulla
Publication year - 2018
Publication title -
applied researches in technics, technologies and education
Language(s) - English
Resource type - Journals
eISSN - 1314-8796
pISSN - 1314-8788
DOI - 10.15547/artte.2018.02.010
Subject(s) - symbolic regression , genetic programming , artificial intelligence , computer science , control (management) , robot , genetic algorithm , machine learning
This paper considers evolutionary methods of symbolic regression for the creation of artificial intelligence of robotic systems. Methods of symbolic regression are reviewed and the features of their application to the solution of the problem of synthesis of control of robotic systems are indicated. The measure of the complexity of artificial intelligence is determined and the advantage of using the principle of small variations of the basic solution is shown, while creating intelligent control systems. A method of variational genetic programming is described and an example of its use for the synthesis of intellectual control is given.