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GECCO
2009
Springer
199views Optimization» more  GECCO 2009»
15 years 11 months ago
Using behavioral exploration objectives to solve deceptive problems in neuro-evolution
Encouraging exploration, typically by preserving the diversity within the population, is one of the most common method to improve the behavior of evolutionary algorithms with dece...
Jean-Baptiste Mouret, Stéphane Doncieux
ICAC
2009
IEEE
16 years 1 months ago
Applying genetic algorithms to decision making in autonomic computing systems
Increasingly, applications need to be able to self-reconfigure in response to changing requirements and environmental conditions. Autonomic computing has been proposed as a means...
Andres J. Ramirez, David B. Knoester, Betty H. C. ...
CEC
2007
IEEE
16 years 20 days ago
Solving multimodal problems via multiobjective techniques with Application to phase equilibrium detection
Abstract— For solving multimodal problems by means of evolutionary algorithms, one often resorts to multistarts or niching methods. The latter approach the question: ‘What is e...
Mike Preuss, Günter Rudolph, Feelly Tumakaka
GECCO
2005
Springer
124views Optimization» more  GECCO 2005»
15 years 12 months ago
Evolving petri nets to represent metabolic pathways
Given concentrations of metabolites over a sequence of time steps, the metabolic pathway prediction problem seeks a set of reactions and rate constants for them that could yield t...
Jeremiah Nummela, Bryant A. Julstrom
KBSE
2007
IEEE
16 years 18 days ago
Improving evolutionary class testing in the presence of non-public methods
Automating the generation of object-oriented unit tests is a challenging task. This is mainly due to the complexity and peculiarities that the principles of object-orientation imp...
Stefan Wappler, Ina Schieferdecker