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GECCO
2011
Springer
264views Optimization» more  GECCO 2011»
12 years 11 months ago
Critical factors in the performance of novelty search
Novelty search is a recently proposed method for evolutionary computation designed to avoid the problem of deception, in which the fitness function guides the search process away...
Steijn Kistemaker, Shimon Whiteson
CEC
2009
IEEE
14 years 2 months ago
Towards creative design using collaborative interactive genetic algorithms
— We present a computational model of creative design based on collaborative interactive genetic algorithms. We test our model on floorplanning. We guide the evolution of floor...
Juan C. Quiroz, Sushil J. Louis, Amit Banerjee, Se...
GECCO
2004
Springer
131views Optimization» more  GECCO 2004»
14 years 23 days ago
PolyEDA: Combining Estimation of Distribution Algorithms and Linear Inequality Constraints
Estimation of distribution algorithms (EDAs) are population-based heuristic search methods that use probabilistic models of good solutions to guide their search. When applied to co...
Jörn Grahl, Franz Rothlauf
FSKD
2005
Springer
180views Fuzzy Logic» more  FSKD 2005»
14 years 27 days ago
An Effective Feature Selection Scheme via Genetic Algorithm Using Mutual Information
Abstract. In the artificial neural networks (ANNs), feature selection is a wellresearched problem, which can improve the network performance and speed up the training of the networ...
Chunkai K. Zhang, Hong Hu
ERCIMDL
2000
Springer
147views Education» more  ERCIMDL 2000»
13 years 11 months ago
Map Segmentation by Colour Cube Genetic K-Mean Clustering
Segmentation of a colour image composed of different kinds of texture regions can be a hard problem, namely to compute for an exact texture fields and a decision of the optimum num...
Vitorino Ramos, Fernando Muge