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» Solving Mastermind Using Genetic Algorithms
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GECCO
2006
Springer
135views Optimization» more  GECCO 2006»
14 years 9 days 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
GECCO
2007
Springer
167views Optimization» more  GECCO 2007»
14 years 2 months ago
An improved restricted growth function genetic algorithm for the consensus clustering of retinal nerve fibre data
This paper describes an extension to the Restricted Growth Function grouping Genetic Algorithm applied to the Consensus Clustering of a retinal nerve fibre layer data-set. Consens...
Stephen Swift, Allan Tucker, Jason Crampton, David...
GECCO
2010
Springer
244views Optimization» more  GECCO 2010»
13 years 8 months ago
Implicit fitness and heterogeneous preferences in the genetic algorithm
This paper takes an economic approach to derive an evolutionary learning model based entirely on the endogenous employment of genetic operators in the service of self-interested a...
Justin T. H. Smith
GECCO
2007
Springer
437views Optimization» more  GECCO 2007»
14 years 2 months ago
A gestalt genetic algorithm: less details for better search
The basic idea to defend in this paper is that an adequate perception of the search space, sacrificing most of the precision, can paradoxically accelerate the discovery of the mo...
Christophe Philemotte, Hugues Bersini
GECCO
2006
Springer
202views Optimization» more  GECCO 2006»
14 years 9 days ago
Inference of genetic networks using S-system: information criteria for model selection
In this paper we present an evolutionary approach for inferring the structure and dynamics in gene circuits from observed expression kinetics. For representing the regulatory inte...
Nasimul Noman, Hitoshi Iba