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 :
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