TY - GEN
T1 - Fine Grained Population Diversity Analysis for Parallel Genetic Programming
AU - Winkler, Stephan
AU - Affenzeller, Michael
AU - Wagner, Stefan
PY - 2009
Y1 - 2009
N2 - In this paper we describe a formalism for estimating the structural similarity of formulas that are evolved by parallel genetic programming (GP) based identification processes. This similarity measurement can be used for measuring the genetic diversity among GP populations and, in the case of multi-population GP, the genetic diversity among sets of GP populations: The higher the average similarity among solutions becomes, the lower is the genetic diversity. Using this definition of genetic diversity for GP we test several different GP based system identification algorithms for analyzing real world measurements of a BMW Diesel engine as well as medical benchmark data taken from the UCI machine learning repository
AB - In this paper we describe a formalism for estimating the structural similarity of formulas that are evolved by parallel genetic programming (GP) based identification processes. This similarity measurement can be used for measuring the genetic diversity among GP populations and, in the case of multi-population GP, the genetic diversity among sets of GP populations: The higher the average similarity among solutions becomes, the lower is the genetic diversity. Using this definition of genetic diversity for GP we test several different GP based system identification algorithms for analyzing real world measurements of a BMW Diesel engine as well as medical benchmark data taken from the UCI machine learning repository
UR - http://www.scopus.com/inward/record.url?scp=70450031254&partnerID=8YFLogxK
U2 - 10.1109/IPDPS.2009.5161117
DO - 10.1109/IPDPS.2009.5161117
M3 - Conference contribution
SN - 9781424437504
T3 - IPDPS 2009 - Proceedings of the 2009 IEEE International Parallel and Distributed Processing Symposium
BT - IPDPS 2009 - Proceedings of the 2009 IEEE International Parallel and Distributed Processing Symposium
T2 - IEEE International Parallel & Distributed Processing Symposium IPDPS 2009
Y2 - 25 May 2009 through 29 May 2009
ER -