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GECCO
2005
Springer
153views Optimization» more  GECCO 2005»
16 years 3 days ago
Evolving neural network ensembles for control problems
In neuroevolution, a genetic algorithm is used to evolve a neural network to perform a particular task. The standard approach is to evolve a population over a number of generation...
David Pardoe, Michael S. Ryoo, Risto Miikkulainen
GECCO
2005
Springer
119views Optimization» more  GECCO 2005»
16 years 3 days ago
Improving GA search reliability using maximal hyper-rectangle analysis
In Genetic algorithms it is not easy to evaluate the confidence level in whether a GA run may have missed a complete area of good points, and whether the global optimum was found....
Chongshan Zhang, Khaled Rasheed
PPSN
2004
Springer
15 years 12 months ago
A Simple Two-Module Problem to Exemplify Building-Block Assembly Under Crossover
Theoretically and empirically it is clear that a genetic algorithm with crossover will outperform a genetic algorithm without crossover in some fitness landscapes, and vice versa i...
Richard A. Watson
SAC
2003
ACM
15 years 11 months ago
Broadcast Program Generation for Unordered Queries with Data Replication
We study in this paper the problem of broadcasting dependent data for unordered queries. However, most prior studies on dependent data broadcasting are limited to the premise of n...
Jiun-Long Huang, Ming-Syan Chen
GECCO
2010
Springer
154views Optimization» more  GECCO 2010»
15 years 11 months ago
Evolutionary learning in networked multi-agent organizations
This study proposes a simple computational model of evolutionary learning in organizations informed by genetic algorithms. Agents who interact only with neighboring partners seek ...
Jae-Woo Kim