@inproceedings{langdon:2005:CECb2p,
title = {Evolving Benchmarks},
address = {Koninklijke Vlaamse Academie van Belgie voor
Wetenschappen en Kunsten, Brussel, Belgium},
author = {W. B. Langdon},
booktitle = {Proceedings of the Seventeenth Belgium/Netherlands
Conference on Artificial Intelligence (BNAIC 2005)},
editor = {Katja Verbeeck and Karl Tuyls and Ann Nowe and Bernard Manderick and Bart Kuijpers},
month = {17-18 October},
pages = {365--366},
publisher = {Royal Flemish Academy of Belgium for Science and Arts,
KVAB},
url = {http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/wbl_bnaic2005.ps.gz},
year = {2005},
abstract = {Genetic programming (GP) is used to evolve global
optimisation test problems. These automatically
generated performance metrics are used to show
strengths and weaknesses of Particle Swarm Optimization
(PSO) and Differential Evolution (DE). Knowledge gained
will help when choosing maximisers (and their tuning
parameters) and in research into new search tools
(which might include hyperheuristics).},
organisation = {BNVKI, Dutch and the Belgian AI Association}, size = {2 pages}, notes = {2 page summary of \cite{langdon:2005:CECb}
http://como.vub.ac.be/bnaic2005/
Described in BNVKI newsletter 22(6) p135.
},
keywords = {algorithm algorithms, analysis, differential evolution genetic optimisation, particle programming, swarm }
}
::