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GECCO
2007
Springer
184views Optimization» more  GECCO 2007»
14 years 2 months ago
Experimental analysis of binary differential evolution in dynamic environments
Many real-world optimization problems are dynamic in nature. The interest in the Evolutionary Algorithms (EAs) community in applying EA variants to dynamic optimization problems h...
Alp Emre Kanlikilicer, Ali Keles, Sima Uyar
GECCO
2007
Springer
177views Optimization» more  GECCO 2007»
14 years 2 months 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
GECCO
2005
Springer
174views Optimization» more  GECCO 2005»
14 years 1 months ago
Coordinating multi-rover systems: evaluation functions for dynamic and noisy environments
This paper addresses the evolution of control strategies for a collective: a set of entities that collectively strives to maximize a global evaluation function that rates the perf...
Kagan Tumer, Adrian K. Agogino
GECCO
2006
Springer
185views Optimization» more  GECCO 2006»
13 years 11 months ago
Memory analysis and significance test for agent behaviours
Many agent problems in a grid world have a restricted sensory information and motor actions. The environmental conditions need dynamic processing of internal memory. In this paper...
DaeEun Kim
GECCO
2005
Springer
154views Optimization» more  GECCO 2005»
14 years 1 months ago
Genetic algorithms using low-discrepancy sequences
The random number generator is one of the important components of evolutionary algorithms (EAs). Therefore, when we try to solve function optimization problems using EAs, we must ...
Shuhei Kimura, Koki Matsumura