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» Plan-Refinement Strategies and Search-Space Size
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ECP
1997
Springer
103views Robotics» more  ECP 1997»
13 years 9 months ago
Plan-Refinement Strategies and Search-Space Size
During the planning process, a planner may have many options for refinements to perform on the plan being developed. The planner’s efficiency depends on how it chooses which ref...
Reiko Tsuneto, Dana S. Nau, James A. Hendler
CEC
2005
IEEE
13 years 10 months ago
On the complexity of overcoming gaps with isotropic mutations and elitist selection
We consider the (1+λ) evolution strategy, an evolutionary algorithm for minimization in Rn , using isotropic mutations. Thus, for instance, Gaussian mutations adapted by the 1/5-r...
Jens Jägersküpper
GECCO
2009
Springer
170views Optimization» more  GECCO 2009»
13 years 9 months ago
Benchmarking a BI-population CMA-ES on the BBOB-2009 noisy testbed
We benchmark the BI-population CMA-ES on the BBOB2009 noisy functions testbed. BI-population refers to a multistart strategy with equal budgets for two interlaced restart strategi...
Nikolaus Hansen
CEC
2003
IEEE
13 years 10 months ago
Homology gives size control in genetic programming
Abstract- The Maximum Homologous Crossover attempts to preserve similar structures from parents by aligning them according to their homology. In this paper, it is successfully test...
Michael Defoin-Platel, Manuel Clergue, Philippe Co...
PPSN
2000
Springer
13 years 8 months ago
An Analysis of Dynamic Severity and Population Size
This work introduces a general mathematical framework for non-stationary fitness functions which enables the exact definition of certain problem properties. The properties' in...
Karsten Weicker