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» An evolutionary method for complex-process optimization
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133
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GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
14 years 10 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
GECCO
2004
Springer
15 years 5 months ago
Validating a Model of Colon Colouration Using an Evolution Strategy with Adaptive Approximations
The colour of colon tissue, which depends on the tissue structure, its optical properties, and the quantities of the pigments present in it, can be predicted by a physics-based mod...
Dzena Hidovic, Jonathan E. Rowe
83
Voted
GECCO
2003
Springer
129views Optimization» more  GECCO 2003»
15 years 5 months ago
Inherent Fault Tolerance in Evolved Sorting Networks
This poster paper summarizes our research on fault tolerance arising as a by-product of the evolutionary computation process. Past research has shown evidence of robustness emergin...
Rob Shepherd, James A. Foster
101
Voted
BMCBI
2008
153views more  BMCBI 2008»
15 years 17 days ago
AWclust: point-and-click software for non-parametric population structure analysis
Background: Population structure analysis is important to genetic association studies and evolutionary investigations. Parametric approaches, e.g. STRUCTURE and L-POP, usually ass...
Xiaoyi Gao, Joshua D. Starmer
99
Voted
GECCO
2008
Springer
122views Optimization» more  GECCO 2008»
15 years 1 months ago
Evolving machine microprograms
The realization of a control unit can be done using a complex circuitry or microprogramming. The latter may be considered as an alternative method of implementation of machine ins...
Pedro A. Castillo Valdivieso, G. Fernández,...