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EVOW
1994
Springer
15 years 6 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 3 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...
134
Voted
ICGA
1993
145views Optimization» more  ICGA 1993»
15 years 3 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 7 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 8 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