Paper Info
Title
BBOB-benchmarking a simple estimation of distribution algorithm with cauchy distribution
Abstract
The restarted estimation of distribution algorithm (EDA) with Cauchy distribution as the probabilistic model is tested on the BBOB 2009 testbed. These tests prove that when using the Cauchy distribution and suitably chosen variance enlargment factor, the algorithm is usable for broad range of fitness landscapes, which is not the case for EDA with Gaussian distribution which converges prematurely. The results of the algorithm are of mixed quality and its scaling is at least quadratic.
Year
DOI
Venue
2009
10.1145/1570256.1570322
GECCO (Companion)
Keywords
Field
DocType
variance enlargment factor,probabilistic model,mixed quality,gaussian distribution,cauchy distribution,broad range,fitness landscape,distribution algorithm,simple estimation,distributed algorithm,estimation of distribution algorithms,estimation of distribution algorithm,benchmarking,local search,evolutionary computation,evolutionary computing
Mathematical optimization,Estimation of distribution algorithm,Quadratic equation,Cauchy distribution,Gaussian,Statistical model,Artificial intelligence,Local search (optimization),Population-based incremental learning,Machine learning,Mathematics,Asymptotic distribution
Conference
Citations 
PageRank 
References 
11
0.85
8
Authors
1
Name
Order
Citations
PageRank
Petr Pošík121015.44