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GECCO
2009
Springer
113views Optimization» more  GECCO 2009»
15 years 4 months ago
Variable size population for dynamic optimization with genetic programming
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. pro...
Leonardo Vanneschi, Giuseppe Cuccu
GECCO
2009
Springer
112views Optimization» more  GECCO 2009»
15 years 6 months ago
Approximating geometric crossover in semantic space
We propose a crossover operator that works with genetic programming trees and is approximately geometric crossover in the semantic space. By defining semantic as program’s eval...
Krzysztof Krawiec, Pawel Lichocki
CEC
2005
IEEE
15 years 1 months ago
Graph composition in a graph grammar-based method for automata network evolution
The dynamics of neural and other automata networks are defined to a large extent by their topologies. Artificial evolution constitutes a practical means by which an optimal topolog...
Martin H. Luerssen, David M. W. Powers
ICMLA
2007
15 years 1 months ago
Improving gene expression programming performance by using differential evolution
Gene Expression Programming (GEP) is an evolutionary algorithm that incorporates both the idea of a simple, linear chromosome of fixed length used in Genetic Algorithms (GAs) and...
Qiongyun Zhang, Chi Zhou, Weimin Xiao, Peter C. Ne...
GECCO
2008
Springer
145views Optimization» more  GECCO 2008»
15 years 21 days ago
Memory with memory: soft assignment in genetic programming
Based in part on observations about the incremental nature of most state changes in biological systems, we introduce the idea of Memory with Memory in Genetic Programming (GP), wh...
Nicholas Freitag McPhee, Riccardo Poli