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» The State Problem for Evolutionary Testing
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ESANN
2007
14 years 11 months ago
Adaptive Global Metamodeling with Neural Networks
Due to the scale and computational complexity of current simulation codes, metamodels (or surrogate models) have become indispensable tools for exploring and understanding the desi...
Dirk Gorissen, Wouter Hendrickx, Tom Dhaene
GECCO
2010
Springer
140views Optimization» more  GECCO 2010»
14 years 10 months ago
Shared memory genetic algorithms in a multi-agent context
In this paper we present a concurrent implementation of genetic algorithms designed for shared memory architectures intended to take advantage of multi-core processor platforms. O...
Dana Vrajitoru
TEC
2002
120views more  TEC 2002»
14 years 9 months ago
Optimization based on bacterial chemotaxis
We present an optimization algorithm based on a model of bacterial chemotaxis. The original biological model is used to formulate a simple optimization algorithm, which is evaluate...
Sibylle D. Müller, Jarno Marchetto, Stefano A...
GECCO
2005
Springer
143views Optimization» more  GECCO 2005»
15 years 3 months ago
Niching in evolution strategies
Evolutionary Algorithms (EAs), popular search methods for solving search and optimization problems, are known for successful and fast location of single optimal solutions. However,...
Ofer M. Shir, Thomas Bäck
GECCO
2010
Springer
151views Optimization» more  GECCO 2010»
15 years 2 months ago
Sustaining behavioral diversity in NEAT
Niching schemes, which sustain population diversity and let an evolutionary population avoid premature convergence, have been extensively studied in the research field of evoluti...
Hirotaka Moriguchi, Shinichi Honiden