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GECCO
2008
Springer
182views Optimization» more  GECCO 2008»
13 years 10 months ago
Scaling ant colony optimization with hierarchical reinforcement learning partitioning
This paper merges hierarchical reinforcement learning (HRL) with ant colony optimization (ACO) to produce a HRL ACO algorithm capable of generating solutions for large domains. Th...
Erik J. Dries, Gilbert L. Peterson
GECCO
2008
Springer
238views Optimization» more  GECCO 2008»
13 years 10 months ago
Using multiple offspring sampling to guide genetic algorithms to solve permutation problems
The correct choice of an evolutionary algorithm, a genetic representation for the problem being solved (as well as their associated variation operators) and the appropriate values...
Antonio LaTorre, José Manuel Peña, V...
GECCO
2008
Springer
107views Optimization» more  GECCO 2008»
13 years 10 months ago
The influence of scaling and assortativity on takeover times in scale-free topologies
In evolving systems, the topological characteristics of population structure have a pronounced impact on the rate of spread of advantageous alleles, and therefore affect selective...
Joshua L. Payne, Margaret J. Eppstein
GECCO
2008
Springer
175views Optimization» more  GECCO 2008»
13 years 10 months ago
Using differential evolution for symbolic regression and numerical constant creation
One problem that has plagued Genetic Programming (GP) and its derivatives is numerical constant creation. Given a mathematical formula expressed as a tree structure, the leaf node...
Brian M. Cerny, Peter C. Nelson, Chi Zhou
GECCO
2008
Springer
184views Optimization» more  GECCO 2008»
13 years 10 months ago
Analysis of mammography reports using maximum variation sampling
A genetic algorithm (GA) was developed to implement a maximum variation sampling technique to derive a subset of data from a large dataset of unstructured mammography reports. It ...
Robert M. Patton, Barbara G. Beckerman, Thomas E. ...
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