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GECCO
2008
Springer
124views Optimization» more  GECCO 2008»
13 years 11 months ago
Aiming for a theoretically tractable CSA variant by means of empirical investigations
Evolution Strategies (ES) for black-box optimization of a function f : Rn → R are investigated. Namely, we consider the cumulative step-size adaptation (CSA) for the variance of...
Jens Jägersküpper, Mike Preuss
GECCO
2008
Springer
110views Optimization» more  GECCO 2008»
13 years 11 months ago
Evolving stable behavior in a spino-neuromuscular system model
This paper demonstrates the effectiveness of genetic algorithms in training stable behavior in a model of the spinoneuromuscular system (SNMS). In particular, we test the stabili...
Stanley Phillips Gotshall, Terry Soule
GECCO
2008
Springer
165views Optimization» more  GECCO 2008»
13 years 11 months ago
Multiple sequence alignment using a GLOCSA guided genetic algorithm
This paper introduces GLOCSA as a new scoring function to rate multiple sequence alignments. It is intended to be simple, considering the whole alignment at once and reflecting t...
Edgar David Arenas-Díaz, Helga Ochoterena-B...
GECCO
2008
Springer
123views Optimization» more  GECCO 2008»
13 years 11 months ago
Hierarchical evolution of linear regressors
We propose an algorithm for function approximation that evolves a set of hierarchical piece-wise linear regressors. The algorithm, named HIRE-Lin, follows the iterative rule learn...
Francesc Teixidó-Navarro, Albert Orriols-Pu...
GECCO
2008
Springer
159views Optimization» more  GECCO 2008»
13 years 11 months ago
IGAP: interactive genetic algorithm peer to peer
We present IGAP, a peer to peer interactive genetic algorithm which reflects the real world methodology followed in team design. We apply our methodology to floorplanning. Throu...
Juan C. Quiroz, Amit Banerjee, Sushil J. Louis