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» Solving iterated functions using genetic programming
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118
Voted
GECCO
2005
Springer
126views Optimization» more  GECCO 2005»
15 years 9 months ago
Not all linear functions are equally difficult for the compact genetic algorithm
Estimation of distribution algorithms (EDAs) try to solve an optimization problem by finding a probability distribution focussed around its optima. For this purpose they conduct ...
Stefan Droste
113
Voted
GECCO
2007
Springer
183views Optimization» more  GECCO 2007»
15 years 9 months ago
Genetic programming for cross-task knowledge sharing
We consider multitask learning of visual concepts within genetic programming (GP) framework. The proposed method evolves a population of GP individuals, with each of them composed...
Wojciech Jaskowski, Krzysztof Krawiec, Bartosz Wie...
EVOW
2004
Springer
15 years 8 months ago
Two-Step Genetic Programming for Optimization of RNA Common-Structure
We present an algorithm for identifying putative non-coding RNA (ncRNA) using an RCSG (RNA Common-Structural Grammar) and show the effectiveness of the algorithm. The algorithm con...
Jin-Wu Nam, Je-Gun Joung, Y. S. Ahn, Byoung-Tak Zh...
GECCO
2004
Springer
158views Optimization» more  GECCO 2004»
15 years 8 months ago
Adaptively Choosing Neighbourhood Bests Using Species in a Particle Swarm Optimizer for Multimodal Function Optimization
This paper proposes an improved particle swarm optimizer using the notion of species to determine its neighbourhood best values, for solving multimodal optimization problems. In th...
Xiaodong Li
CEC
2008
IEEE
15 years 10 months ago
A study on constrained MA using GA and SQP: Analytical vs. finite-difference gradients
— Many deterministic algorithms in the context of constrained optimization require the first-order derivatives, or the gradient vectors, of the objective and constraint function...
Stephanus Daniel Handoko, Chee Keong Kwoh, Yew-Soo...