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GECCO
2006
Springer
180views Optimization» more  GECCO 2006»
15 years 11 months ago
Improving cooperative GP ensemble with clustering and pruning for pattern classification
A boosting algorithm based on cellular genetic programming to build an ensemble of predictors is proposed. The method evolves a population of trees for a fixed number of rounds an...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...
GECCO
2006
Springer
124views Optimization» more  GECCO 2006»
15 years 11 months ago
On evolving buffer overflow attacks using genetic programming
In this work, we employed genetic programming to evolve a "white hat" attacker; that is to say, we evolve variants of an attack with the objective of providing better de...
Hilmi Günes Kayacik, Malcolm I. Heywood, A. N...
GECCO
2006
Springer
218views Optimization» more  GECCO 2006»
15 years 11 months ago
A survey of mutation techniques in genetic programming
The importance of mutation varies across evolutionary computation domains including: genetic programming, evolution strategies, and genetic algorithms. In the genetic programming ...
Alan Piszcz, Terence Soule
GECCO
2006
Springer
139views Optimization» more  GECCO 2006»
15 years 11 months ago
Genetic programming: optimal population sizes for varying complexity problems
The population size in evolutionary computation is a significant parameter affecting computational effort and the ability to successfully evolve solutions. We find that population...
Alan Piszcz, Terence Soule
GECCO
2006
Springer
205views Optimization» more  GECCO 2006»
15 years 11 months ago
Alternative evolutionary algorithms for evolving programs: evolution strategies and steady state GP
In contrast with the diverse array of genetic algorithms, the Genetic Programming (GP) paradigm is usually applied in a relatively uniform manner. Heuristics have developed over t...
L. Darrell Whitley, Marc D. Richards, J. Ross Beve...
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