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» A new crossover technique for Cartesian genetic programming
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GECCO
2011
Springer
248views Optimization» more  GECCO 2011»
12 years 11 months ago
Size-based tournaments for node selection
In genetic programming, the reproductive operators of crossover and mutation both require the selection of nodes from the reproducing individuals. Both unbiased random selection a...
Thomas Helmuth, Lee Spector, Brian Martin
IICAI
2003
13 years 8 months ago
The Acyclic Bayesian Net Generator
Abstract. We present the Acyclic Bayesian Net Generator, a new approach to learn the structure of a Bayesian network using genetic algorithms. Due to the encoding mechanism, acycli...
Pankaj B. Gupta, Vicki H. Allan
ICANNGA
2007
Springer
138views Algorithms» more  ICANNGA 2007»
14 years 1 months ago
Liquid State Genetic Programming
Abstract. A new Genetic Programming variant called Liquid State Genetic Programming (LSGP) is proposed in this paper. LSGP is a hybrid method combining a dynamic memory for storing...
Mihai Oltean
GECCO
2008
Springer
119views Optimization» more  GECCO 2008»
13 years 8 months ago
GP age-layer and crossover effects in bid-offer spread prediction
The bid-offer spread on equity options is a key source of profits for market makers, and a key cost for those trading in the options. Spreads are influenced by dynamic market f...
Amy Willis, Suneer Patel, Christopher D. Clack
EVOW
1994
Springer
13 years 11 months ago
Genetic Approaches to Learning Recursive Relations
The genetic programming (GP) paradigm is a new approach to inductively forming programs that describe a particular problem. The use of natural selection based on a fitness ]unction...
Peter A. Whigham, Robert I. McKay