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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
SIES
2007
IEEE
14 years 2 months ago
Design Space Exploration with Evolutionary Multi-Objective Optimisation
— High level synthesis is one of the next major steps to improve the hw/sw co-design process. The advantages of high nthesis are two-fold. At first the level of abstraction is r...
Martin Holzer 0002, Bastian Knerr, Markus Rupp
CIG
2006
IEEE
13 years 10 months ago
Improving Artificial Intelligence In a Motocross Game
We have previously investigated the use of artificial neural networks to ride simulated motorbikes in a new computer game. These artificial neural networks were trained using two d...
Benoit Chaperot, Colin Fyfe
CEC
2009
IEEE
14 years 2 months ago
Performance assessment of the hybrid Archive-based Micro Genetic Algorithm (AMGA) on the CEC09 test problems
— In this paper, the performance assessment of the hybrid Archive-based Micro Genetic Algorithm (AMGA) on a set of bound-constrained synthetic test problems is reported. The hybr...
Santosh Tiwari, Georges Fadel, Patrick Koch, Kalya...
GECCO
2009
Springer
144views Optimization» more  GECCO 2009»
14 years 2 months ago
Cheating for problem solving: a genetic algorithm with social interactions
We propose a variation of the standard genetic algorithm that incorporates social interaction between the individuals in the population. Our goal is to understand the evolutionary...
Rafael Lahoz-Beltra, Gabriela Ochoa, Uwe Aickelin