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» GAS, A Concept on Modeling Species in Genetic Algorithms
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GECCO
2003
Springer
137views Optimization» more  GECCO 2003»
14 years 18 days ago
The Spatially-Dispersed Genetic Algorithm
Abstract. Spatially structured population models improve the performance of genetic algorithms by assisting the selection scheme in maintaining diversity. A significant concern wi...
Grant Dick
GECCO
2007
Springer
164views Optimization» more  GECCO 2007»
14 years 1 months ago
Is the island model fault tolerant?
In this paper, we present a study on the fault tolerance nature of the island model when applied to Genetic Algorithms. Parallel and distributed models have been extensively appli...
José Ignacio Hidalgo, Juan Lanchares, Franc...
AAAI
1998
13 years 8 months ago
Fast Probabilistic Modeling for Combinatorial Optimization
Probabilistic models have recently been utilized for the optimization of large combinatorial search problems. However, complex probabilistic models that attempt to capture interpa...
Shumeet Baluja, Scott Davies
EC
2006
195views ECommerce» more  EC 2006»
13 years 7 months ago
Automated Global Structure Extraction for Effective Local Building Block Processing in XCS
Learning Classifier Systems (LCSs), such as the accuracy-based XCS, evolve distributed problem solutions represented by a population of rules. During evolution, features are speci...
Martin V. Butz, Martin Pelikan, Xavier Llorà...
GECCO
2005
Springer
150views Optimization» more  GECCO 2005»
14 years 25 days ago
A GA for maximum likelihood phylogenetic inference using neighbour-joining as a genotype to phenotype mapping
Evolutionary relationships among species can be represented by a phylogenetic tree and inferred by optimising some measure of fitness, such as the statistical likelihood of the t...
Leon Poladian