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CORR
2010
Springer
152views Education» more  CORR 2010»
13 years 9 months ago
Neuroevolutionary optimization
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
Eva Volná
EMO
2009
Springer
235views Optimization» more  EMO 2009»
14 years 3 months ago
Bi-objective Optimization for the Vehicle Routing Problem with Time Windows: Using Route Similarity to Enhance Performance
Abstract. The Vehicle Routing Problem with Time Windows is a complex combinatorial optimization problem which can be seen as a fusion of two well known sub-problems: the Travelling...
Abel Garcia-Najera, John A. Bullinaria
GECCO
2007
Springer
153views Optimization» more  GECCO 2007»
14 years 3 months ago
Analyzing the effects of module encapsulation on search space bias
Modularity is thought to improve the evolvability of biological systems [18, 22]. Recent studies in the field of evolutionary computation show that the use of modularity improves...
Ozlem O. Garibay, Annie S. Wu
ICML
2003
IEEE
14 years 2 months ago
Evolutionary MCMC Sampling and Optimization in Discrete Spaces
The links between genetic algorithms and population-based Markov Chain Monte Carlo (MCMC) methods are explored. Genetic algorithms (GAs) are well-known for their capability to opt...
Malcolm J. A. Strens
CEC
2003
IEEE
14 years 2 months ago
Comparing neural networks and Kriging for fitness approximation in evolutionary optimization
Neural networks and the Kriging method are compared for constructing £tness approximation models in evolutionary optimization algorithms. The two models are applied in an identica...
Lars Willmes, Thomas Bäck, Yaochu Jin, Bernha...