DocumentCode
2728759
Title
Tree swarm optimization: an approach to PSO-based tree discovery
Author
Veenhuis, Christian ; Köppen, Mario ; Kruger, Jörg ; Nickolay, Bertram
Author_Institution
Fraunhofer IPK, Berlin, Germany
Volume
2
fYear
2005
fDate
2-5 Sept. 2005
Firstpage
1238
Abstract
In recent years a swarm-based optimization methodology called particle swarm optimization (PSO) has developed. PSO is highly explorative and primarily used in function optimization. This paper proposes a swarm-based learning algorithm based on PSO which is able to discover trees in tree spaces. Particles are flying through a tree space forming flocks around peaks of a fitness function. Because it inherits the explorative property of PSO, it needs only few evaluations to find suitable trees.
Keywords
learning (artificial intelligence); particle swarm optimisation; trees (mathematics); fitness function; function optimization; particle swarm optimization; swarm-based learning algorithm; tree discovery; tree spaces; tree swarm optimization; Ant colony optimization; Assembly; Birds; Classification tree analysis; Decision trees; Genetic programming; Machine learning; Machine learning algorithms; Optimization methods; Particle swarm optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2005. The 2005 IEEE Congress on
Print_ISBN
0-7803-9363-5
Type
conf
DOI
10.1109/CEC.2005.1554832
Filename
1554832
Link To Document