118 search results - page 13 / 24 » Fitness Clouds and Problem Hardness in Genetic Programming |
GECCO
2005
Springer
14 years 1 months ago
2005
Springer
We present a molecular computing algorithm for evolving DNA-encoded genetic programs in a test tube. The use of synthetic DNA molecules combined with biochemical techniques for va...
EUROGP
2009
Springer
14 years 2 months ago
2009
Springer
Self Modifying CGP (SMCGP) is a developmental form of Cartesian Genetic Programming(CGP). It is able to modify its own phenotype during execution of the evolved program. This is do...
CORR
2006
Springer
13 years 7 months ago
2006
Springer
Abstract. Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed opti...
GECCO
2006
Springer
13 years 11 months ago
2006
Springer
Previous research has shown that evolutionary systems not only try to develop solutions that satisfy a fitness requirement, but indirectly attempt to develop genetically robust so...
GECCO
2008
Springer
13 years 8 months ago
2008
Springer
We investigated how indexed FOR-loops, such as the ones found in procedural programming languages, can be implemented in genetic programming. We use them to train programs that le...