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164
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GECCO
2007
Springer
185views Optimization» more  GECCO 2007»
16 years 9 days ago
An informed convergence accelerator for evolutionary multiobjective optimiser
A novel optimisation accelerator deploying neural network predictions and objective space direct manipulation strategies is presented. The concept of directing the search through ...
Salem F. Adra, Ian Griffin, Peter J. Fleming
GECCO
2007
Springer
181views Optimization» more  GECCO 2007»
16 years 9 days ago
A study on metamodeling techniques, ensembles, and multi-surrogates in evolutionary computation
Surrogate-Assisted Memetic Algorithm(SAMA) is a hybrid evolutionary algorithm, particularly a memetic algorithm that employs surrogate models in the optimization search. Since mos...
Dudy Lim, Yew-Soon Ong, Yaochu Jin, Bernhard Sendh...
150
Voted
GECCO
2007
Springer
178views Optimization» more  GECCO 2007»
16 years 9 days ago
Nonlinear dynamics modelling for controller evolution
The problem of how to acquire a model of a physical robot, which is fit for evolution of controllers that can subsequently be used to control that robot, is considered in the con...
Julian Togelius, Renzo De Nardi, Hugo Gravato Marq...
GECCO
2007
Springer
177views Optimization» more  GECCO 2007»
16 years 9 days ago
Evolving virtual creatures revisited
Thirteen years have passed since Karl Sims published his work on evolving virtual creatures. Since then, several novel approaches to neural network evolution and genetic algorithm...
Peter Krcah
ICANN
2007
Springer
16 years 9 days ago
Sparse Least Squares Support Vector Regressors Trained in the Reduced Empirical Feature Space
Abstract. In this paper we discuss sparse least squares support vector regressors (sparse LS SVRs) defined in the reduced empirical feature space, which is a subspace of mapped tr...
Shigeo Abe, Kenta Onishi