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GECCO
1999
Springer
15 years 2 months ago
Large Populations Are Not Always The Best Choice In Genetic Programming
In genetic programming a general consensus is that the population should be as large as practically possible or sensible. In this paper we examine a batch of problems of combinato...
Matthias Fuchs
GECCO
2007
Springer
159views Optimization» more  GECCO 2007»
15 years 3 months ago
A systemic computation platform for the modelling and analysis of processes with natural characteristics
Computation in biology and in conventional computer architectures seem to share some features, yet many of their important characteristics are very different. To address this, [1]...
Erwan Le Martelot, Peter J. Bentley, R. Beau Lotto
GECCO
2009
Springer
258views Optimization» more  GECCO 2009»
15 years 2 months ago
Evolutionary learning of local descriptor operators for object recognition
Nowadays, object recognition is widely studied under the paradigm of matching local features. This work describes a genetic programming methodology that synthesizes mathematical e...
Cynthia B. Pérez, Gustavo Olague
CEC
2008
IEEE
15 years 4 months ago
Geometric PSO + GP = Particle Swarm Programming
—Geometric particle swarm optimization (GPSO) is a recently introduced formal generalization of traditional particle swarm optimization (PSO) that applies naturally to both conti...
Julian Togelius, Renzo De Nardi, Alberto Moraglio
GPEM
2006
97views more  GPEM 2006»
14 years 9 months ago
Evolving recursive programs by using adaptive grammar based genetic programming
Genetic programming (GP) extends traditional genetic algorithms to automatically induce computer programs. GP has been applied in a wide range of applications such as software ree...
Man Wong