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» Fitness Clouds and Problem Hardness in Genetic Programming
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ICML
1994
IEEE
14 years 13 days ago
Hierarchical Self-Organization in Genetic programming
This paper presents an approach to automatic discovery of functions in Genetic Programming. The approach is based on discovery of useful building blocks by analyzing the evolution...
Justinian P. Rosca, Dana H. Ballard
GECCO
2010
Springer
220views Optimization» more  GECCO 2010»
14 years 7 days ago
Interday foreign exchange trading using linear genetic programming
Foreign exchange (forex) market trading using evolutionary algorithms is an active and controversial area of research. We investigate the use of a linear genetic programming (LGP)...
Garnett Carl Wilson, Wolfgang Banzhaf
EVOW
2009
Springer
13 years 6 months ago
Conquering the Needle-in-a-Haystack: How Correlated Input Variables Beneficially Alter the Fitness Landscape for Neural Networks
Abstract. Evolutionary algorithms such as genetic programming and grammatical evolution have been used for simultaneously optimizing network architecture, variable selection, and w...
Stephen D. Turner, Marylyn D. Ritchie, William S. ...
GPEM
2010
180views more  GPEM 2010»
13 years 7 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
GECCO
2006
Springer
185views Optimization» more  GECCO 2006»
14 years 17 days ago
Convergence to global optima for genetic programming systems with dynamically scaled operators
This work shows asymptotic convergence to global optima for a family of dynamically scaled genetic programming systems where the underlying population consists of a fixed number o...
Lothar M. Schmitt, Stefan Droste