GECCO
2006
Springer
14 years 7 days ago
2006
Springer
GECCO
2006
Springer
14 years 7 days ago
2006
Springer
Two mathematical and two computational theories from the field of human and animal learning are combined to produce a more general theory of adaptive behavior. The cornerstone of ...
GECCO
2006
Springer
14 years 7 days ago
2006
Springer
Genetic algorithms (GAs) have recently become very popular by solving combinatorial optimization problems. In this paper, we propose an extension of the hybrid genetic algorithm f...
GECCO
2006
Springer
14 years 7 days ago
2006
Springer
Various applications of spectral techniques for enhancing graph bisection in genetic algorithms are investigated. Several enhancements to a genetic algorithm for graph bisection a...
GECCO
2006
Springer
14 years 7 days ago
2006
Springer
In this paper we embed evolutionary computation into statistical learning theory. First, we outline the connection between large margin optimization and statistical learning and s...
GECCO
2006
Springer
14 years 7 days ago
2006
Springer
Estimation of Distribution Algorithms (EDAs) are a class of evolutionary algorithms that use machine learning techniques to solve optimization problems. Machine learning is used t...
GECCO
2006
Springer
14 years 7 days ago
2006
Springer
The representation used by a learning algorithm introduces a bias which is more or less well-suited to any given learning problem. It is well known that, across all possible probl...
GECCO
2006
Springer
14 years 7 days ago
2006
Springer
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...
GECCO
2006
Springer
14 years 7 days ago
2006
Springer
In this paper, we present an empirical comparison of some Differential Evolution variants to solve global optimization problems. The aim is to identify which one of them is more s...
GECCO
2006
Springer
14 years 7 days ago
2006
Springer