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» On the Brittleness of Evolutionary Algorithms
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GECCO
2006
Springer
139views Optimization» more  GECCO 2006»
15 years 3 months ago
Genetic programming: optimal population sizes for varying complexity problems
The population size in evolutionary computation is a significant parameter affecting computational effort and the ability to successfully evolve solutions. We find that population...
Alan Piszcz, Terence Soule
GECCO
2010
Springer
173views Optimization» more  GECCO 2010»
15 years 3 months ago
The baldwin effect in developing neural networks
The Baldwin Effect is a very plausible, but unproven, biological theory concerning the power of learning to accelerate evolution. Simple computational models in the 1980’s gave...
Keith L. Downing
EVOW
2000
Springer
15 years 3 months ago
Prediction of Power Requirements for High-Speed Circuits
Modern VLSI design methodologies and manufacturing technologies are making circuits increasingly fast. The quest for higher circuit performance and integration density stems from f...
Fulvio Corno, Maurizio Rebaudengo, Matteo Sonza Re...
GCB
2000
Springer
137views Biometrics» more  GCB 2000»
15 years 3 months ago
Detecting Sporadic Recombination in DNA Alignments with Hidden Markov Models
Conventional phylogenetic tree estimation methods assume that all sites in a DNA multiple alignment have the same evolutionary history. This assumption is violated in data sets fro...
Dirk Husmeier, Frank Wright
SPIRE
2000
Springer
15 years 3 months ago
Virtual Test Tubes: A New Methodology for Computing
Biomolecular computing (BMC) aims to capture the innumerable advantages that biological molecules have gained in the course of millions of years of evolution to perform computatio...
Max H. Garzon, Evan Drumwright, Russell J. Deaton,...