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» Convergence of Program Fitness Landscapes
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EVOW
2009
Springer
13 years 2 months ago
Conquering the Needle-in-a-Haystack: How Correlated Input Variables Beneficially Alter the Fitness Landscape for Neural Networks
Abstract. Evolutionary algorithms such as genetic programming and grammatical evolution have been used for simultaneously optimizing network architecture, variable selection, and w...
Stephen D. Turner, Marylyn D. Ritchie, William S. ...
GECCO
2000
Springer
178views Optimization» more  GECCO 2000»
13 years 8 months ago
Fitness Sharing in Genetic Programming
This paper investigates fitness sharing in genetic programming. Implicit fitness sharing is applied to populations of programs. Three treatments are compared: raw fitness, pure fi...
Robert I. McKay
GECCO
2006
Springer
166views Optimization» more  GECCO 2006»
13 years 8 months ago
Comparing genetic robustness in generational vs. steady state evolutionary algorithms
Previous research has shown that evolutionary systems not only try to develop solutions that satisfy a fitness requirement, but indirectly attempt to develop genetically robust so...
Josh Jones, Terry Soule
FLAIRS
2004
13 years 6 months ago
Multimodal Function Optimization Using Local Ruggedness Information
In multimodal function optimization, niching techniques create diversification within the population, thus encouraging heterogeneous convergence. The key to the effective diversif...
Jian Zhang 0007, Xiaohui Yuan, Bill P. Buckles
GECCO
2004
Springer
13 years 10 months ago
Fitness Clouds and Problem Hardness in Genetic Programming
This paper presents an investigation of genetic programming fitness landscapes. We propose a new indicator of problem hardness for tree-based genetic programming, called negative ...
Leonardo Vanneschi, Manuel Clergue, Philippe Colla...