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GECCO
2006
Springer
206views Optimization» more  GECCO 2006»
15 years 1 months ago
Adaptive discretization for probabilistic model building genetic algorithms
This paper proposes an adaptive discretization method, called Split-on-Demand (SoD), to enable the probabilistic model building genetic algorithm (PMBGA) to solve optimization pro...
Chao-Hong Chen, Wei-Nan Liu, Ying-Ping Chen
COR
2006
122views more  COR 2006»
14 years 10 months ago
Multiple task assignments for cooperating uninhabited aerial vehicles using genetic algorithms
A problem of assigning cooperating uninhabited aerial vehicles to perform multiple tasks on multiple targets is posed as a new combinatorial optimization problem. A genetic algori...
Tal Shima, Steven J. Rasmussen, Andrew G. Sparks, ...
GECCO
2006
Springer
148views Optimization» more  GECCO 2006»
15 years 1 months ago
Behavioural GP diversity for dynamic environments: an application in hedge fund investment
We present a new mechanism for preserving phenotypic behavioural diversity in a Genetic Programming application for hedge fund portfolio optimization, and provide experimental res...
Wei Yan, Christopher D. Clack
SIAMCOMP
2011
14 years 4 months ago
Self-Improving Algorithms
We investigate ways in which an algorithm can improve its expected performance by fine-tuning itself automatically with respect to an arbitrary, unknown input distribution. We gi...
Nir Ailon, Bernard Chazelle, Kenneth L. Clarkson, ...
GECCO
2005
Springer
116views Optimization» more  GECCO 2005»
15 years 3 months ago
Terrain generation using genetic algorithms
We propose a method for applying genetic algorithms to create 3D terrain data sets. Existing procedural algorithms for generation of terrain have several shortcomings. The most po...
TeongJoo Ong, Ryan Saunders, John Keyser, John J. ...