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» Introduction to genetic programming
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ICCS
2004
Springer
15 years 3 months ago
Designing Digital Circuits for the Knapsack Problem
Abstract. Multi Expression Programming (MEP) is a Genetic Programming variant that uses linear chromosomes for solution encoding. A unique feature of MEP is its ability of encoding...
Mihai Oltean, Crina Grosan, Mihaela Oltean
PRL
2007
200views more  PRL 2007»
14 years 9 months ago
Generative learning of visual concepts using multiobjective genetic programming
This paper introduces a novel method of visual learning based on Genetic Programming, which evolves a population of individuals (image analysis programs) that process attributed v...
Krzysztof Krawiec
CEC
2008
IEEE
15 years 4 months ago
Evolution of image filters on graphics processor units using Cartesian Genetic Programming
— Graphics processor units are fast, inexpensive parallel computing devices. Recently there has been great interest in harnessing this power for various types of scientific comp...
Simon Harding
KES
2000
Springer
15 years 1 months ago
On AIE-ASM: a software to simulate artificial stock markets with genetic programming
Agent-based computational economic modeling requires demanding work on computer programming. Usually, the publications as outcomes of running these programs do not provide readers ...
Shu-Heng Chen, Chung-Chih Liao, Chia-Hsuan Yeh
GECCO
2007
Springer
176views Optimization» more  GECCO 2007»
15 years 3 months ago
Best SubTree genetic programming
The result of the program encoded into a Genetic Programming (GP) tree is usually returned by the root of that tree. However, this is not a general strategy. In this paper we pres...
Oana Muntean, Laura Diosan, Mihai Oltean