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GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
13 years 3 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
GECCO
2008
Springer
238views Optimization» more  GECCO 2008»
13 years 6 months ago
Using multiple offspring sampling to guide genetic algorithms to solve permutation problems
The correct choice of an evolutionary algorithm, a genetic representation for the problem being solved (as well as their associated variation operators) and the appropriate values...
Antonio LaTorre, José Manuel Peña, V...
CEC
2007
IEEE
13 years 11 months ago
Graph design by graph grammar evolution
— Determining the optimal topology of a graph is pertinent to many domains, as graphs can be used to model a variety of systems. Evolutionary algorithms constitute a popular opti...
Martin H. Luerssen, David M. W. Powers
GECCO
2007
Springer
177views Optimization» more  GECCO 2007»
13 years 11 months ago
Evolving virtual creatures revisited
Thirteen years have passed since Karl Sims published his work on evolving virtual creatures. Since then, several novel approaches to neural network evolution and genetic algorithm...
Peter Krcah
APIN
1998
107views more  APIN 1998»
13 years 5 months ago
Multiple Adaptive Agents for Tactical Driving
Abstract. Recent research in automated highway systems has ranged from low-level vision-based controllers to high-level route-guidance software. However, there is currently no syst...
Rahul Sukthankar, Shumeet Baluja, John Hancock