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GECCO
2005
Springer
136views Optimization» more  GECCO 2005»
14 years 1 months ago
Exploring extended particle swarms: a genetic programming approach
Particle Swarm Optimisation (PSO) uses a population of particles that fly over the fitness landscape in search of an optimal solution. The particles are controlled by forces tha...
Riccardo Poli, Cecilia Di Chio, William B. Langdon
GECCO
2005
Springer
151views Optimization» more  GECCO 2005»
14 years 1 months ago
Backward-chaining genetic programming
Tournament selection is the most frequently used form of selection in genetic programming (GP). Tournament selection chooses individuals uniformly at random from the population. A...
Riccardo Poli, William B. Langdon
GECCO
2008
Springer
174views Optimization» more  GECCO 2008»
13 years 8 months ago
Mask functions for the symbolic modeling of epistasis using genetic programming
The study of common, complex multifactorial diseases in genetic epidemiology is complicated by nonlinearity in the genotype-to-phenotype mapping relationship that is due, in part,...
Ryan J. Urbanowicz, Nate Barney, Bill C. White, Ja...
GECCO
2008
Springer
111views Optimization» more  GECCO 2008»
13 years 8 months ago
Multi-task code reuse in genetic programming
We propose a method of knowledge reuse between evolutionary processes that solve different optimization tasks. We define the method in the framework of tree-based genetic progra...
Wojciech Jaskowski, Krzysztof Krawiec, Bartosz Wie...
FGCS
2010
119views more  FGCS 2010»
13 years 6 months ago
Characterizing fault tolerance in genetic programming
Evolutionary Algorithms, including Genetic Programming (GP), are frequently employed to solve difficult real-life problems, which can require up to days or months of computation. ...
Daniel Lombraña Gonzalez, Francisco Fern&aa...