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» Fitness Sharing in Genetic Programming
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EVOW
2009
Springer
13 years 5 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. ...
GECCO
2007
Springer
283views Optimization» more  GECCO 2007»
14 years 1 months ago
Evolving Lucene search queries for text classification
We describe a method for generating accurate, compact, human understandable text classifiers. Text datasets are indexed using Apache Lucene and Genetic Programs are used to constr...
Laurence Hirsch, Robin Hirsch, Masoud Saeedi
EVOW
1994
Springer
13 years 11 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
GECCO
2010
Springer
158views Optimization» more  GECCO 2010»
13 years 11 months ago
Efficiently evolving programs through the search for novelty
A significant challenge in genetic programming is premature convergence to local optima, which often prevents evolution from solving problems. This paper introduces to genetic pro...
Joel Lehman, Kenneth O. Stanley
GECCO
2006
Springer
135views Optimization» more  GECCO 2006»
13 years 11 months ago
Single and multi-objective genetic operators in object-oriented conceptual software design
This poster paper investigates the potential of single and multiobjective genetic operators with an object-oriented conceptual design space. Using cohesion as an objective fitness...
Christopher L. Simons, Ian C. Parmee