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CIDM
2007
IEEE
15 years 4 months ago
K2GA: Heuristically Guided Evolution of Bayesian Network Structures from Data
— We present K2GA, an algorithm for learning Bayesian network structures from data. K2GA uses a genetic algorithm to perform stochastic search, while employing a modified versio...
Eli Faulkner
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
GECCO
2008
Springer
148views Optimization» more  GECCO 2008»
14 years 10 months ago
Combining cartesian genetic programming with an estimation of distribution algorithm
This paper describes initial testing of a novel idea to combine a CGP with an EDA. In recent work a new improved crossover technique was successfully applied to a CGP. To implemen...
Janet Clegg
EUROGP
2005
Springer
122views Optimization» more  EUROGP 2005»
15 years 3 months ago
Evolution of Robot Controller Using Cartesian Genetic Programming
Abstract. Cartesian Genetic Programming is a graph based representation that has many benefits over traditional tree based methods, including bloat free evolution and faster evolu...
Simon Harding, Julian F. Miller
87
Voted
PPSN
2004
Springer
15 years 3 months ago
Optimization via Parameter Mapping with Genetic Programming
Abstract. This paper describes a new approach for parameter optimization that uses a novel representation for the parameters to be optimized. By using genetic programming, the new ...
João Carlos Figueira Pujol, Riccardo Poli