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GPEM
2000
121views more  GPEM 2000»
13 years 7 months ago
Bayesian Methods for Efficient Genetic Programming
ct. A Bayesian framework for genetic programming GP is presented. This is motivated by the observation that genetic programming iteratively searches populations of fitter programs ...
Byoung-Tak Zhang
GPEM
2002
163views more  GPEM 2002»
13 years 7 months ago
Fast Ant Colony Optimization on Runtime Reconfigurable Processor Arrays
Ant Colony Optimization (ACO) is a metaheuristic used to solve combinatorial optimization problems. As with other metaheuristics, like evolutionary methods, ACO algorithms often sh...
Daniel Merkle, Martin Middendorf
GPEM
2002
104views more  GPEM 2002»
13 years 7 months ago
Genetic Programming-based Construction of Features for Machine Learning and Knowledge Discovery Tasks
In this paper we use genetic programming for changing the representation of the input data for machine learners. In particular, the topic of interest here is feature construction i...
Krzysztof Krawiec
GPEM
2010
180views more  GPEM 2010»
13 years 6 months ago
Developments in Cartesian Genetic Programming: self-modifying CGP
Abstract Self-Modifying Cartesian Genetic Programming (SMCGP) is a general purpose, graph-based, developmental form of Genetic Programming founded on Cartesian Genetic Programming....
Simon Harding, Julian F. Miller, Wolfgang Banzhaf
GPEM
2010
89views more  GPEM 2010»
13 years 6 months ago
Variable population size and evolution acceleration: a case study with a parallel evolutionary algorithm
Abstract With current developments of parallel and distributed computing, evolutionary algorithms have benefited considerably from parallelization techniques. Besides improved com...
Ting Hu, Simon Harding, Wolfgang Banzhaf