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» On the practical genetic algorithms
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GECCO
1999
Springer
14 years 23 days ago
Large Populations Are Not Always The Best Choice In Genetic Programming
In genetic programming a general consensus is that the population should be as large as practically possible or sensible. In this paper we examine a batch of problems of combinato...
Matthias Fuchs
AIEDAM
2008
102views more  AIEDAM 2008»
13 years 8 months ago
Machine invention of quantum computing circuits by means of genetic programming
We demonstrate the use of genetic programming in the automatic invention of quantum computing circuits that solve problems of potential theoretical and practical significance. We ...
Lee Spector, Jon Klein
ICANN
2001
Springer
14 years 1 months ago
A Computational Intelligence Approach to Optimization with Unknown Objective Functions
In many practical engineering design problems, the form of objective function is not given explicitly in terms of design variables. Given the value of design variables, under this ...
Hirotaka Nakayama, Masao Arakawa, Rie Sasaki
GECCO
2009
Springer
142views Optimization» more  GECCO 2009»
14 years 1 months ago
Evolution, development and learning using self-modifying cartesian genetic programming
Self-Modifying Cartesian Genetic Programming (SMCGP) is a form of genetic programming that integrates developmental (self-modifying) features as a genotype-phenotype mapping. This...
Simon Harding, Julian Francis Miller, Wolfgang Ban...
CODES
2004
IEEE
14 years 7 days ago
Power-aware communication optimization for networks-on-chips with voltage scalable links
Networks-on-Chip (NoC) is emerging as a practical development platform for future systems-on-chip products. We propose an energyefficient static algorithm which optimizes the ener...
Dongkun Shin, Jihong Kim