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GECCO
2009
Springer
103views Optimization» more  GECCO 2009»
14 years 10 days ago
Using performance fronts for parameter setting of stochastic metaheuristics
In this work, we explore the idea that parameter setting of stochastic metaheuristics should be considered as a multiobjective problem. The so-called “performance fronts” pres...
Johann Dréo
GECCO
2004
Springer
134views Optimization» more  GECCO 2004»
14 years 1 months ago
A Descriptive Encoding Language for Evolving Modular Neural Networks
Evolutionary algorithms are a promising approach for the automated design of artificial neural networks, but they require a compact and efficient genetic encoding scheme to repres...
Jae-Yoon Jung, James A. Reggia
EOR
2006
135views more  EOR 2006»
13 years 7 months ago
Principles of scatter search
Scatter search is an evolutionary method that has been successfully applied to hard optimization problems. The fundamental concepts and principles of the method were first propose...
Rafael Martí, Manuel Laguna, Fred Glover
GECCO
2010
Springer
233views Optimization» more  GECCO 2010»
14 years 16 days ago
Evolutionary-based conflict-free scheduling of collective communications on spidergon NoCs
The Spidergon interconnection network has become popular recently in multiprocessor systems on chips. To the best of our knowledge, algorithms for collective communications (CC) h...
Jirí Jaros, Vaclav Dvorak
CEC
2007
IEEE
14 years 2 months ago
Parallel learning in heterogeneous multi-robot swarms
Abstract— Designing effective behavioral controllers for mobile robots can be difficult and tedious; this process can be circumvented by using unsupervised learning techniques w...
Jim Pugh, Alcherio Martinoli