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» Code Compaction Using Genetic Algorithms
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CEC
2008
IEEE
13 years 11 months ago
Investigation of simply coded evolutionary artificial neural networks on robot control problems
One of the advantages of evolutionary robotics over other approaches in embodied cognitive science would be its parallel population search. Due to the population search, it takes a...
Yoshiaki Katada, Jun Nakazawa
GECCO
2005
Springer
114views Optimization» more  GECCO 2005»
14 years 3 months ago
Exploiting disruption aversion to control code bloat
The authors employ multiple crossovers as a novel natural extension to crossovers as a mixing operator. They use this as a framework to explore the ideas of code growth. Empirical...
Jason Stevens, Robert B. Heckendorn, Terence Soule
GECCO
2008
Springer
133views Optimization» more  GECCO 2008»
13 years 10 months ago
Automatic generation of XSLT stylesheets using evolutionary algorithms
This paper introduces a procedure based on genetic programming to evolve XSLT programs (usually called stylesheets or logicsheets). XSLT is a general purpose, document-oriented fu...
Pablo García-Sánchez, Juan Juli&aacu...
GECCO
2006
Springer
213views Optimization» more  GECCO 2006»
14 years 1 months ago
Evolutionary unit testing of object-oriented software using strongly-typed genetic programming
Evolutionary algorithms have successfully been applied to software testing. Not only approaches that search for numeric test data for procedural test objects have been investigate...
Stefan Wappler, Joachim Wegener
GECCO
2004
Springer
134views Optimization» more  GECCO 2004»
14 years 3 months ago
A Descriptive Encoding Language for Evolving Modular Neural Networks
Evolutionary algorithms are a promising approach for the automated design of artificial neural networks, but they require a compact and efficient genetic encoding scheme to repres...
Jae-Yoon Jung, James A. Reggia