A new model of Genetic Programming with variable size population is presented in this paper and applied to the reconstruction of target functions in dynamic environments (i.e. problems where target functions change with time). The suitability of this model is tested on a set of benchmarks based on some well known symbolic regression problems. Experimental results confirm that our variable size population model finds solutions of similar quality to the ones found by standard Genetic Programming, but with a smaller amount of computational effort.
Vanneschi, L., Cuccu, G. (2009). A study of genetic programming variable population size for dynamic optimization problems. In Proceedings of the International Joint Conference on Computational Intelligence (IJCCI 2009), Madeira, Portugal, 5-7 October 2009 (pp.119-126).
A study of genetic programming variable population size for dynamic optimization problems
VANNESCHI, LEONARDO;
2009
Abstract
A new model of Genetic Programming with variable size population is presented in this paper and applied to the reconstruction of target functions in dynamic environments (i.e. problems where target functions change with time). The suitability of this model is tested on a set of benchmarks based on some well known symbolic regression problems. Experimental results confirm that our variable size population model finds solutions of similar quality to the ones found by standard Genetic Programming, but with a smaller amount of computational effort.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
