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» Dynamic Control of Genetic Algorithms in a Noisy Environment
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GECCO
1999
Springer
158views Optimization» more  GECCO 1999»
13 years 11 months ago
Coevolutionary Genetic Algorithms for Solving Dynamic Constraint Satisfaction Problems
In this paper, we discuss the adaptability of Coevolutionary Genetic Algorithms on dynamic environments. Our CGA consists of two populations: solution-level one and schema-level o...
Hisashi Handa, Osamu Katai, Tadataka Konishi, Mits...
ISCC
2006
IEEE
188views Communications» more  ISCC 2006»
14 years 1 months ago
Dejong Function Optimization by Means of a Parallel Approach to Fuzzified Genetic Algorithm
Genetic Algorithms are very powerful search methods that are used in different optimization problems. Parallel versions of genetic algorithms are easily implemented and usually in...
Ebrahim Bagheri, Hossein Deldari
ROMAN
2007
IEEE
131views Robotics» more  ROMAN 2007»
14 years 1 months ago
Real-time acoustic source localization in noisy environments for human-robot multimodal interaction
— Interaction between humans involves a plethora of sensory information, both in the form of explicit communication as well as more subtle unconsciously perceived signals. In ord...
Vlad M. Trifa, Ansgar Koene, Jan Morén, Gor...
GECCO
2005
Springer
118views Optimization» more  GECCO 2005»
14 years 28 days ago
G2DGA: an adaptive framework for internet-based distributed genetic algorithms
The Internet is different from traditional parallel computing environments, and Distributed Genetic Algorithms (DGAs) for the Internet need to be designed to address these diffe...
Johan Berntsson
GECCO
2000
Springer
145views Optimization» more  GECCO 2000»
13 years 11 months ago
Enhancing the GA's Ability to Cope with Dynamic Environments
: The Shifting Balance Genetic Algorithm (SBGA) is a pluggable module for a GA (or any other Evolutionary Algorithm) based on a modification of Sewall Wright's shifting balanc...
Mark Wineberg, Franz Oppacher