8 search results - page 1 / 2 » Probabilistic distribution models for EDA-based GP |
GECCO
2007
Springer
13 years 10 months ago
2007
Springer
Markov Networks (also known as Markov Random Fields) have been proposed as a new approach to probabilistic modelling in Estimation of Distribution Algorithms (EDAs). An EDA employ...
CEC
2009
IEEE
13 years 9 months ago
2009
IEEE
— The protein structure prediction (PSP) problem is one of the most important problems in computational biology. This paper proposes a novel Estimation of Distribution Algorithms...
GECCO
2008
Springer
13 years 5 months ago
2008
Springer
The key ideas behind most of the recently proposed Markov networks based EDAs were to factorise the joint probability distribution in terms of the cliques in the undirected graph....
GECCO
2005
Springer
13 years 10 months ago
2005
Springer
This paper proposes a novel technique for a program evolution based on probabilistic models. In the proposed method, two probabilistic distribution models with probabilistic depen...
CEC
2009
IEEE
13 years 11 months ago
2009
IEEE
—Structure learning is a crucial component of a multivariate Estimation of Distribution algorithm. It is the part which determines the interactions between variables in the proba...