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CEC
2005
IEEE
13 years 9 months ago
Population based incremental learning with guided mutation versus genetic algorithms: iterated prisoners dilemma
Axelrod’s original experiments for evolving IPD player strategies involved the use of a basic GA. In this paper we examine how well a simple GA performs against the more recent P...
Timothy Gosling, Nanlin Jin, Edward P. K. Tsang
GECCO
2006
Springer
159views Optimization» more  GECCO 2006»
13 years 11 months ago
Smart crossover operator with multiple parents for a Pittsburgh learning classifier system
This paper proposes a new smart crossover operator for a Pittsburgh Learning Classifier System. This operator, unlike other recent LCS approaches of smart recombination, does not ...
Jaume Bacardit, Natalio Krasnogor
AUSAI
2004
Springer
14 years 22 days ago
Genetic Algorithm Based K-Means Fast Learning Artificial Neural Network
The K-means Fast Learning Artificial Neural Network (KFLANN) is a small neural network bearing two types of parameters, the tolerance, δ and the vigilance, µ. In previous papers,...
Yin Xiang, Alex Leng Phuan Tay
GECCO
2006
Springer
156views Optimization» more  GECCO 2006»
13 years 11 months ago
Improving GP classifier generalization using a cluster separation metric
Genetic Programming offers freedom in the definition of the cost function that is unparalleled among supervised learning algorithms. However, this freedom goes largely unexploited...
Ashley George, Malcolm I. Heywood
CEC
2005
IEEE
13 years 9 months ago
On the use of rule-sharing in learning classifier system ensembles
This paper presents an investigation into exploiting the population-based nature of Learning Classifier Systems for their use within highly-parallel systems. In particular, the use...
Larry Bull, Matthew Studley, Anthony J. Bagnall, I...