Evolutionary Identification of Active Particle Systems
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Stanciulescu:2000:WSCG,
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author = "Bogdan Stanciulescu and Jean Louchet",
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title = "Evolutionary Identification of Active Particle
Systems",
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booktitle = "International Conference in Central Europe on Computer
Graphics, Visualization and Interactive Digital Media,
WSCG 2000",
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year = "2000",
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editor = "Nadia Magnenat Thalmann and Vaclav Skala",
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address = "Plzen, Czech Republic",
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month = "7-10 " # feb,
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organisation = "University of West Bohemia",
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keywords = "genetic algorithms, genetic programming, computer
animation, computer graphics, physically based motion
modelling, particle-based modelling, evolutionary
strategies, motion analysis, neural networks, ANN,
neural controllers",
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URL = "http://wscg.zcu.cz/wscg2000/Papers_2000/T43.ps.gz",
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size = "8 pages",
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abstract = "This paper presents how it is possible to introduce
active motricity into particle-bond systems used in
applications such as image animation. We chose to add
into some neural network capabilities over the
classical approach, in order to obtain a system able to
model a larger class of behaviour. Therefore a new type
of binary bond enriched with a neural-based command
ability is proposed and tested in this paper. This
active bond acts like a controlled muscle in order to
produce motricity. An Evolutionary Strategy is used to
optimise the particle-bond system parameters through
evolving parameter sets. We tested our method both on
artificially generated data and on data collected from
real-life motion. Results and comparisons between our
method and other approaches show the advantage of using
active particle-bond systems for image animation
applications.",
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notes = "Horse muscles
http://wscg.zcu.cz/wscg2000/wscg2000.htm EUROGRAPHICS
and IFIP WG 5.10
also known as \cite{DBLP:conf/wscg/StanciulescuL00}",
- }
Genetic Programming entries for
Bogdan Stanciulescu
Jean Louchet
Citations