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GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
14 years 7 months ago
Uncertainty handling CMA-ES for reinforcement learning
The covariance matrix adaptation evolution strategy (CMAES) has proven to be a powerful method for reinforcement learning (RL). Recently, the CMA-ES has been augmented with an ada...
Verena Heidrich-Meisner, Christian Igel
KBSE
2005
IEEE
15 years 3 months ago
Properties and scopes in web model checking
We consider a formal framework for property verification of web applications using Spin model checker. Some of the web related properties concern all states of the model, while ot...
May Haydar, Sergiy Boroday, Alexandre Petrenko, Ho...
GECCO
2006
Springer
159views Optimization» more  GECCO 2006»
15 years 1 months ago
Multi-step environment learning classifier systems applied to hyper-heuristics
Heuristic Algorithms (HA) are very widely used to tackle practical problems in operations research. They are simple, easy to understand and inspire confidence. Many of these HAs a...
Javier G. Marín-Blázquez, Sonia Schu...
GECCO
2007
Springer
156views Optimization» more  GECCO 2007»
15 years 4 months ago
Techniques for highly multiobjective optimisation: some nondominated points are better than others
The research area of evolutionary multiobjective optimization (EMO) is reaching better understandings of the properties and capabilities of EMO algorithms, and accumulating much e...
David W. Corne, Joshua D. Knowles
KES
2004
Springer
15 years 3 months ago
Extracting Stellar Population Parameters of Galaxies from Photometric Data Using Evolution Strategies and Locally Weighted Linea
There is now a huge amount of high quality photometric data available in the literature whose analysis is bound to play a fundamental role in studies of the formation and evolution...
Luis Alvarez, Olac Fuentes, Roberto Terlevich