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GECCO
2004
Springer
126views Optimization» more  GECCO 2004»
15 years 3 months ago
A Gene Based Adaptive Mutation Strategy for Genetic Algorithms
In this study, a new mechanism that adapts the mutation rate for each locus on the chromosomes, based on feedback obtained from the current population is proposed. Through tests us...
Sima Uyar, Sanem Sariel, Gülsen Eryigit
GECCO
2004
Springer
15 years 3 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...
GECCO
2004
Springer
15 years 3 months ago
Subthreshold-Seeking Behavior and Robust Local Search
Subthreshold-seeking behavior occurs when the majority of the points that an algorithm samples have an evaluation less than some target threshold. We characterize sets of functions...
L. Darrell Whitley, Keith Bush, Jonathan E. Rowe
GECCO
2004
Springer
175views Optimization» more  GECCO 2004»
15 years 3 months ago
Enhanced Innovation: A Fusion of Chance Discovery and Evolutionary Computation to Foster Creative Processes and Decision Making
Abstract. Human-based genetic algorithms are powerful tools for organizational modeling. If we enhance them using chance discovery techniques, we obtain an innovative approach for ...
Xavier Llorà, Kei Ohnishi, Ying-Ping Chen, ...
GECCO
2004
Springer
118views Optimization» more  GECCO 2004»
15 years 3 months ago
Adapting Representation in Genetic Programming
Genetic Programming uses trees to represent chromosomes. The user defines the representation space by defining the set of functions and terminals to label the nodes in the trees....
Cezary Z. Janikow