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GECCO
2008
Springer
183views Optimization» more  GECCO 2008»
13 years 10 months ago
UMDAs for dynamic optimization problems
This paper investigates how the Univariate Marginal Distribution Algorithm (UMDA) behaves in non-stationary environments when engaging in sampling and selection strategies designe...
Carlos M. Fernandes, Cláudio F. Lima, Agost...
GECCO
2008
Springer
114views Optimization» more  GECCO 2008»
13 years 10 months ago
Strategic positioning in tactical scenario planning
Capability planning problems are pervasive throughout many areas of human interest with prominent examples found in defense and security. Planning provides a unique context for op...
James M. Whitacre, Hussein A. Abbass, Ruhul A. Sar...
GECCO
2008
Springer
199views Optimization» more  GECCO 2008»
13 years 10 months ago
Analysis of multi-objective evolutionary algorithms to optimize dynamic data types in embedded systems
New multimedia embedded applications are increasingly dynamic, and rely on Dynamically-allocated Data Types (DDTs) to store their data. The optimization of DDTs for each target em...
José Ignacio Hidalgo, José L. Risco-...
GECCO
2008
Springer
135views Optimization» more  GECCO 2008»
13 years 10 months ago
Context-dependent predictions and cognitive arm control with XCSF
While John Holland has always envisioned learning classifier systems (LCSs) as cognitive systems, most work on LCSs has focused on classification, datamining, and function appro...
Martin V. Butz, Oliver Herbort
GECCO
2008
Springer
143views Optimization» more  GECCO 2008»
13 years 10 months ago
Application domain study of evolutionary algorithms in optimization problems
This paper deals with the problem of comparing and testing evolutionary algorithms, that is, the benchmarking problem, from an analysis point of view. A practical study of the app...
Pilar Caamaño, Francisco Bellas, José...
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