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GECCO
2008
Springer
116views Optimization» more  GECCO 2008»
13 years 8 months ago
Stock trading strategies by genetic network programming with flag nodes
Genetic Network Programming (GNP) has been proposed as a graph-based evolutionary algorithm. GNP works well especially in dynamic environments due to its graph structures. In addi...
Shingo Mabu, Yan Chen, Etsushi Ohkawa, Kotaro Hira...
GECCO
2006
Springer
173views Optimization» more  GECCO 2006»
13 years 11 months ago
Pareto-coevolutionary genetic programming classifier
The conversion and extension of the Incremental ParetoCoevolution Archive algorithm (IPCA) into the domain of Genetic Programming classifier evolution is presented. In order to ac...
Michal Lemczyk, Malcolm I. Heywood
DMIN
2006
142views Data Mining» more  DMIN 2006»
13 years 8 months ago
Parallel Hybrid Clustering using Genetic Programming and Multi-Objective Fitness with Density (PYRAMID)
Clustering is the process of locating patterns in large data sets. It is an active research area that provides value to scientific as well as business applications. Practical clust...
Junping Sun, William Sverdlik, Samir Tout
ICDCS
2003
IEEE
14 years 21 days ago
Compiler Scheduling of Mobile Agents for Minimizing Overheads
Mobile code carried by a mobile agent can automatically travel to several data sources in order to complete a designated program. Traditionally, most mobile agent systems [7][8][1...
Xiaotong Zhuang, Santosh Pande
GECCO
2008
Springer
130views Optimization» more  GECCO 2008»
13 years 8 months ago
Parsimony pressure made easy
The parsimony pressure method is perhaps the simplest and most frequently used method to control bloat in genetic programming. In this paper we first reconsider the size evolutio...
Riccardo Poli, Nicholas Freitag McPhee