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GECCO
2007
Springer
276views Optimization» more  GECCO 2007»
15 years 3 months ago
Meta-optimizing semantic evolutionary search
I present MOSES (meta-optimizing semantic evolutionary search), a new probabilistic modeling (estimation of distribution) approach to program evolution. Distributions are not esti...
Moshe Looks
GECCO
2007
Springer
160views Optimization» more  GECCO 2007»
15 years 3 months ago
A memetic algorithm for the low autocorrelation binary sequence problem
Finding binary sequences with low autocorrelation is a very hard problem with many practical applications. In this paper we analyze several metaheuristic approaches to tackle the ...
José E. Gallardo, Carlos Cotta, Antonio J. ...
94
Voted
EVOW
2007
Springer
15 years 1 months ago
An Evolutionary Approach to Computer-Aided Orchestration
In this paper we introduce an hybrid evolutionary algorithm for computer-aided orchestration. Our current approach to orchestration consists in replicating a target sound with a se...
Grégoire Carpentier, Damien Tardieu, G&eacu...
77
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GECCO
2005
Springer
154views Optimization» more  GECCO 2005»
15 years 3 months ago
The molecule evoluator: an interactive evolutionary algorithm for designing drug molecules
To help chemists design new drugs, we created a tool that uses interactive evolution to design drug molecules, the “Molecule Evoluator”. In contrast to most other evolutionary...
Eric-Wubbo Lameijer, Adriaan P. IJzerman, Joost N....
GECCO
2007
Springer
182views Optimization» more  GECCO 2007»
15 years 3 months ago
An analysis of the effects of population structure on scalable multiobjective optimization problems
Multiobjective evolutionary algorithms (MOEA) are an effective tool for solving search and optimization problems containing several incommensurable and possibly conflicting objec...
Michael Kirley, Robert L. Stewart