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EVOW
1994
Springer
15 years 3 months ago
Genetic Approaches to Learning Recursive Relations
The genetic programming (GP) paradigm is a new approach to inductively forming programs that describe a particular problem. The use of natural selection based on a fitness ]unction...
Peter A. Whigham, Robert I. McKay
ICMLA
2007
15 years 1 months ago
Improving gene expression programming performance by using differential evolution
Gene Expression Programming (GEP) is an evolutionary algorithm that incorporates both the idea of a simple, linear chromosome of fixed length used in Genetic Algorithms (GAs) and...
Qiongyun Zhang, Chi Zhou, Weimin Xiao, Peter C. Ne...
ICGA
1993
145views Optimization» more  ICGA 1993»
15 years 1 months ago
Genetic Programming of Minimal Neural Nets Using Occam's Razor
A genetic programming method is investigated for optimizing both the architecture and the connection weights of multilayer feedforward neural networks. The genotype of each networ...
Byoung-Tak Zhang, Heinz Mühlenbein
CEC
2005
IEEE
15 years 5 months ago
Linear genetic programming using a compressed genotype representation
This paper presents a modularization strategy for linear genetic programming (GP) based on a substring compression/substitution scheme. The purpose of this substitution scheme is t...
Johan Parent, Ann Nowé, Kris Steenhaut, Ann...
CEC
2009
IEEE
15 years 6 months ago
Representation and structural biases in CGP
— An evolutionary algorithm automatically discovers suitable solutions to a problem, which may lie anywhere in a large search space of candidate solutions. In the case of Genetic...
Andrew J. Payne, Susan Stepney