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GECCO
2007
Springer
177views Optimization» more  GECCO 2007»
14 years 1 months ago
Evolving problem heuristics with on-line ACGP
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
GECCO
2007
Springer
213views Optimization» more  GECCO 2007»
14 years 1 months ago
Genetically programmed learning classifier system description and results
An agent population can be evolved in a complex environment to perform various tasks and optimize its job performance using Learning Classifier System (LCS) technology. Due to the...
Gregory Anthony Harrison, Eric W. Worden
GECCO
2005
Springer
158views Optimization» more  GECCO 2005»
14 years 1 months ago
Constructive induction and genetic algorithms for learning concepts with complex interaction
Constructive Induction is the process of transforming the original representation of hard concepts with complex interaction into a representation that highlights regularities. Mos...
Leila Shila Shafti, Eduardo Pérez
GECCO
2003
Springer
14 years 25 days ago
Quad Search and Hybrid Genetic Algorithms
A bit climber using a Gray encoding is guaranteed to converge to a global optimum in fewer than ¢¤£¦¥¨§© evaluations on unimodal 1-D functions and on multi-dimensional sph...
L. Darrell Whitley, Deon Garrett, Jean-Paul Watson
AAAI
1996
13 years 9 months ago
Evolution-Based Discovery of Hierarchical Behaviors
Procedural representations of control policies have two advantages when facing the scale-up problem in learning tasks. First they are implicit, with potential for inductive genera...
Justinian P. Rosca, Dana H. Ballard