Sciweavers

151 search results - page 23 / 31
» Seeding Genetic Programming Populations
Sort
View
IPPS
2006
IEEE
14 years 1 months ago
Multiple sequence alignment by quantum genetic algorithm
In this paper we describe a new approach for the well known problem in bioinformatics: Multiple Sequence Alignment (MSA). MSA is fundamental task as it represents an essential pla...
L. Abdesslem, M. Soham, B. Mohamed
EUROGP
2009
Springer
119views Optimization» more  EUROGP 2009»
14 years 2 months ago
Comparison of CGP and Age-Layered CGP Performance in Image Operator Evolution
This paper analyses the efficiency of the Cartesian Genetic Programming (CGP) methodology in the image operator design problem at the functional level. The CGP algorithm is compare...
Karel Slaný
GECCO
2006
Springer
166views Optimization» more  GECCO 2006»
13 years 11 months ago
Comparing genetic robustness in generational vs. steady state evolutionary algorithms
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...
Josh Jones, Terry Soule
CEC
2010
IEEE
12 years 11 months ago
Tweaking a tower of blocks leads to a TMBL: Pursuing long term fitness growth in program evolution
— If a population of programs evolved not for a few hundred generations but for a few hundred thousand or more, could it generate more interesting behaviours and tackle more comp...
Tony E. Lewis, George D. Magoulas
GECCO
2010
Springer
191views Optimization» more  GECCO 2010»
13 years 7 months ago
Fitness importance for online evolution
To complement standard fitness functions, we propose "Fitness Importance" (FI) as a novel meta-heuristic for online learning systems. We define FI and show how it can be...
Philip Valencia, Raja Jurdak, Peter Lindsay