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GECCO
2008
Springer
183views Optimization» more  GECCO 2008»
14 years 11 months ago
UMDAs for dynamic optimization problems
This paper investigates how the Univariate Marginal Distribution Algorithm (UMDA) behaves in non-stationary environments when engaging in sampling and selection strategies designe...
Carlos M. Fernandes, Cláudio F. Lima, Agost...
GECCO
2005
Springer
150views Optimization» more  GECCO 2005»
15 years 3 months ago
Population-based incremental learning with memory scheme for changing environments
In recent years there has been a growing interest in studying evolutionary algorithms for dynamic optimization problems due to its importance in real world applications. Several a...
Shengxiang Yang
ERCIMDL
2000
Springer
147views Education» more  ERCIMDL 2000»
15 years 1 months ago
Map Segmentation by Colour Cube Genetic K-Mean Clustering
Segmentation of a colour image composed of different kinds of texture regions can be a hard problem, namely to compute for an exact texture fields and a decision of the optimum num...
Vitorino Ramos, Fernando Muge
GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
14 years 7 months ago
Uncertainty handling CMA-ES for reinforcement learning
The covariance matrix adaptation evolution strategy (CMAES) has proven to be a powerful method for reinforcement learning (RL). Recently, the CMA-ES has been augmented with an ada...
Verena Heidrich-Meisner, Christian Igel
ICCD
1999
IEEE
130views Hardware» more  ICCD 1999»
15 years 2 months ago
Preference-Driven Hierarchical Hardware/Software Partitioning
In this paper, we present a hierarchical evolutionary approach to hardware/software partitioning for real-time embedded systems. In contrast to most of previous approaches, we app...
Gang Quan, Xiaobo Hu, Garrison W. Greenwood