Title :
Choosing Best Fitness Function with Reinforcement Learning
Author :
Afanasyeva, Arina ; Buzdalov, Maxim
Author_Institution :
Nat. Res. Univ. of Inf. Technol., Mech. & Opt., St. Petersburg, Russia
Abstract :
This paper describes an optimization problem with one target function to be optimized and several supporting functions that can be used to speed up the optimization process. A method based on reinforcement learning is proposed for choosing a good supporting function during optimization using genetic algorithm. Results of applying this method to a model problem are shown.
Keywords :
genetic algorithms; learning (artificial intelligence); mathematics computing; fitness function; genetic algorithm; optimization problem; reinforcement learning; Computational modeling; Genetic algorithms; Heuristic algorithms; Learning; Machine learning; Optimization; Switches;
Conference_Titel :
Machine Learning and Applications and Workshops (ICMLA), 2011 10th International Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
978-1-4577-2134-2
DOI :
10.1109/ICMLA.2011.163
