Name
Abstract | ||
|---|---|---|
Of late, much progress has been made in developing Estimation of Distribution Algorithms (EDA), algorithms that use probabilistic modelling of high quality solutions to guide their search. While experimental results on EDA behaviour are widely available, theoretical results are still rare. This is especially the case for continuous EDA. In this article, we develop theory that predicts the behaviour of the Univariate Marginal Distribution, Algorithm in the continuous domain (UMDA(c)) with truncation selection on monotonous fitness functions. Monotonous functions are commonly used to model the algorithm behaviour far from the optimum. Our result includes formulae to predict population statistics in a specific generation as well as population statistics after convergence. We find that population statistics develop identically for monotonous functions. We show that if assuming monotonous fitness functions, the distance that UMDA(c) travels across the search space is bounded and solely relies on the percentage of selected individuals and not on the structure of the fitness landscape. This can be problematic if this distance is too small for the algorithm to find the optimum. Also, by wrongly setting the selection intensity, one might not be able to explore the whole search space. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/CEC.2005.1555014 | 2005 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-3, PROCEEDINGS |
Keywords | Field | DocType |
statistical analysis,estimation of distribution algorithm,monotone function,development theory,search space,evolutionary computation,estimation theory | Convergence (routing),Truncation selection,Mathematical optimization,Fitness landscape,Estimation of distribution algorithm,Evolutionary computation,Artificial intelligence,Estimation theory,Probabilistic modelling,Mathematics,Machine learning,Bounded function | Conference |
Citations | PageRank | References |
23 | 1.44 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jörn Grahl | 1 | 194 | 15.68 |
| Stefan Minner | 2 | 362 | 41.63 |
| Franz Rothlauf | 3 | 1497 | 160.29 |