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GECCO
2005
Springer
110views Optimization» more  GECCO 2005»
16 years 9 days ago
Towards identifying populations that increase the likelihood of success in genetic programming
This paper presents a comprehensive, multivariate account of how initial population material is used over the course of a genetic programming run as while various factors influenc...
Jason M. Daida
GECCO
2005
Springer
137views Optimization» more  GECCO 2005»
16 years 9 days ago
Constant generation for the financial domain using grammatical evolution
This study reports the work to date on the analysis of different methodologies for constant creation with the aim of applying the most advantageous method to the dynamic real wor...
Ian Dempsey
GECCO
2005
Springer
175views Optimization» more  GECCO 2005»
16 years 9 days ago
Meta-grammar constant creation with grammatical evolution by grammatical evolution
This study examines the utility of meta-grammar constant generation on a series of benchmark problems. The performance of the meta-grammar approach is compared to a grammar which ...
Ian Dempsey, Michael O'Neill, Anthony Brabazon
GECCO
2005
Springer
16 years 9 days ago
Intelligent exploration method for XCS
Exploration/Exploitation equilibrium is one of the most challenging issues in reinforcement learning area as well as learning classifier systems such as XCS. In this paper1 , an i...
Ali Hamzeh, Adel Rahmani
MCS
2005
Springer
16 years 8 days ago
Ensembles of Classifiers from Spatially Disjoint Data
We describe an ensemble learning approach that accurately learns from data that has been partitioned according to the arbitrary spatial requirements of a large-scale simulation whe...
Robert E. Banfield, Lawrence O. Hall, Kevin W. Bow...