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» The Evolutionary Control Methodology: An Overview
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GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
13 years 5 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
METRICS
2005
IEEE
14 years 1 months ago
Visualizing Historical Data Using Spectrographs
Studying the evolution of long lived processes such as the development history of a software system or the publication history of a research community, requires the analysis of a ...
Ahmed E. Hassan, Jingwei Wu, Richard C. Holt
GECCO
2005
Springer
134views Optimization» more  GECCO 2005»
14 years 1 months ago
Tracking extrema in dynamic environments using a coevolutionary agent-based model of genotype edition
Typical applications of evolutionary optimization in static environments involve the approximation of the extrema of functions. For dynamic environments, the interest is not to lo...
Chien-Feng Huang, Luis Mateus Rocha
GECCO
2006
Springer
192views Optimization» more  GECCO 2006»
13 years 11 months ago
Optimising cancer chemotherapy using an estimation of distribution algorithm and genetic algorithms
This paper presents a methodology for using heuristic search methods to optimise cancer chemotherapy. Specifically, two evolutionary algorithms - Population Based Incremental Lear...
Andrei Petrovski, Siddhartha Shakya, John A. W. Mc...
DATE
2006
IEEE
95views Hardware» more  DATE 2006»
14 years 1 months ago
An effective technique for minimizing the cost of processor software-based diagnosis in SoCs
The ever increasing usage of microprocessor devices is sustained by a high volume production that in turn requires a high production yield, backed by a controlled process. Fault d...
Paolo Bernardi, Ernesto Sánchez, Massimilia...