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» Fitness Clouds and Problem Hardness in Genetic Programming
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GECCO
2006
Springer
181views Optimization» more  GECCO 2006»
13 years 11 months ago
Designing safe, profitable automated stock trading agents using evolutionary algorithms
Trading rules are widely used by practitioners as an effective means to mechanize aspects of their reasoning about stock price trends. However, due to the simplicity of these rule...
Harish Subramanian, Subramanian Ramamoorthy, Peter...
GECCO
2004
Springer
160views Optimization» more  GECCO 2004»
14 years 1 months ago
Finding Effective Software Metrics to Classify Maintainability Using a Parallel Genetic Algorithm
The ability to predict the quality of a software object can be viewed as a classification problem, where software metrics are the features and expert quality rankings the class lab...
Rodrigo A. Vivanco, Nicolino J. Pizzi
GECCO
2006
Springer
206views Optimization» more  GECCO 2006»
13 years 11 months ago
A dynamically constrained genetic algorithm for hardware-software partitioning
In this article, we describe the application of an enhanced genetic algorithm to the problem of hardware-software codesign. Starting from a source code written in a high-level lan...
Pierre-André Mudry, Guillaume Zufferey, Gia...
PRL
2006
139views more  PRL 2006»
13 years 7 months ago
Evolving color constancy
Objects retain their color in spite of changes in the wavelength and energy composition of the light they reflect. This phenomenon is called color constancy and plays an important ...
Marc Ebner
IWCLS
2007
Springer
14 years 1 months ago
On Lookahead and Latent Learning in Simple LCS
Learning Classifier Systems use evolutionary algorithms to facilitate rule- discovery, where rule fitness is traditionally payoff based and assigned under a sharing scheme. Most c...
Larry Bull