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» Evolutionary Neuroestimation of Fitness Functions
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GECCO
2005
Springer
131views Optimization» more  GECCO 2005»
14 years 7 days ago
EA models and population fixed-points versus mutation rates for functions of unitation
Using a dynamic systems model for the Simple Genetic Algorithm due to Vose[1], we analyze the fixed point behavior of the model without crossover applied to functions of unitation...
J. Neal Richter, John Paxton, Alden H. Wright
GECCO
1999
Springer
142views Optimization» more  GECCO 1999»
13 years 11 months ago
Towards Byte Code Genetic Programming
This paper uses the GP paradigm to evolve linear genotypes (individuals) that consist of Java byte code. Our prototype GP system is implemented in Java using a standard Java devel...
Brad Harvey, James A. Foster, Deborah A. Frincke
ISMB
1994
13 years 8 months ago
Evolution of a Computer Program for Classifying Protein Segments as Transmembrane Domains Using Genetic Programming
The recently-developedgenetic programming paradigmisused to evoIve a computer program to classify a given protein segment as being a transmembrane domainor non-uansmembranearea of...
John R. Koza
GECCO
2004
Springer
14 years 3 days ago
Hybridizing Evolutionary Testing with the Chaining Approach
Fitness functions derived for certain white-box test goals can cause problems for Evolutionary Testing (ET), due to a lack of sufficient guidance to the required test data. Often t...
Phil McMinn, Mike Holcombe
EH
2002
IEEE
112views Hardware» more  EH 2002»
13 years 11 months ago
Evolving Circuits in Seconds: Experiments with a Stand-Alone Board-Level Evolvable System
The purpose of this paper is twofold: first, to illustrate a stand-alone board-level evolvable system (SABLES) and its performance, and second to illustrate some problems that occ...
Adrian Stoica, Ricardo Salem Zebulum, Michael I. F...