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GECCO
2007
Springer
183views Optimization» more  GECCO 2007»
14 years 3 months ago
Distribution replacement: how survival of the worst can out perform survival of the fittest
A new family of "Distribution Replacement” operators for use in steady state genetic algorithms is presented. Distribution replacement enforces the members of the populatio...
Howard Tripp, Phil Palmer
GECCO
2010
Springer
244views Optimization» more  GECCO 2010»
13 years 9 months ago
Implicit fitness and heterogeneous preferences in the genetic algorithm
This paper takes an economic approach to derive an evolutionary learning model based entirely on the endogenous employment of genetic operators in the service of self-interested a...
Justin T. H. Smith
GECCO
2006
Springer
195views Optimization» more  GECCO 2006»
14 years 25 days ago
Studying XCS/BOA learning in Boolean functions: structure encoding and random Boolean functions
Recently, studies with the XCS classifier system on Boolean functions have shown that in certain types of functions simple crossover operators can lead to disruption and, conseque...
Martin V. Butz, Martin Pelikan
GECCO
2006
Springer
215views Optimization» more  GECCO 2006»
14 years 25 days ago
A multi-chromosome approach to standard and embedded cartesian genetic programming
Embedded Cartesian Genetic Programming (ECGP) is an extension of Cartesian Genetic Programming (CGP) that can automatically acquire, evolve and re-use partial solutions in the for...
James Alfred Walker, Julian Francis Miller, Rachel...
DAC
2006
ACM
14 years 10 months ago
Design automation for DNA self-assembled nanostructures
DNA self-assembly is an emerging technology with potential as a future replacement of conventional lithographic fabrication. A key challenge is the specification of appropriate DN...
Constantin Pistol, Alvin R. Lebeck, Chris Dwyer