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ICANN
2007
Springer
16 years 8 hour ago
Evolutionary Multi-objective Optimization of Spiking Neural Networks
Evolutionary multi-objective optimization of spiking neural networks for solving classification problems is studied in this paper. By means of a Paretobased multi-objective geneti...
Yaochu Jin, Ruojing Wen, Bernhard Sendhoff
GECCO
2004
Springer
15 years 11 months ago
Dynamic Uniform Scaling for Multiobjective Genetic Algorithms
Before Multiobjective EvolutionaryAlgorithms (MOEAs) can be used as a widespread tool for solving arbitrary real world problems there are some salient issues which require further ...
Gerulf K. M. Pedersen, David E. Goldberg
GECCO
1999
Springer
145views Optimization» more  GECCO 1999»
15 years 10 months ago
Three Ways to Grow Designs: A Comparison of Embryogenies for an Evolutionary Design Problem
This paper explores the use of growth processes, or embryogenies, to map genotypes to phenotypes within evolutionary systems. Following a summary of the significant features of em...
Peter J. Bentley, Sanjeev Kumar
GECCO
2010
Springer
347views Optimization» more  GECCO 2010»
15 years 7 months ago
Comparison of cauchy EDA and BIPOP-CMA-ES algorithms on the BBOB noiseless testbed
Estimation-of-distribution algorithm using Cauchy sampling distribution is compared with the bi-population CMA evolutionary strategy which was one of the best contenders in the bl...
Petr Posík
PPSN
2004
Springer
15 years 11 months ago
Statistical Racing Techniques for Improved Empirical Evaluation of Evolutionary Algorithms
In empirical studies of Evolutionary Algorithms, it is usually desirable to evaluate and compare algorithms using as many different parameter settings and test problems as possible...
Bo Yuan, Marcus Gallagher