Self-organizing primitives for automated shape composition
Created by W.Langdon from
gp-bibliography.bib Revision:1.8028
- @InProceedings{Bai:2008:ieeeSMI,
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author = "Linge Bai and Manolya Eyiyurekli and David E. Breen",
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title = "Self-organizing primitives for automated shape
composition",
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booktitle = "IEEE International Conference on Shape Modeling and
Applications, SMI 2008",
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year = "2008",
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month = jun,
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pages = "147--154",
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keywords = "genetic algorithms, genetic programming, automated
shape composition, cell behavior, chemical-field-driven
aggregation, chemotaxis-driven aggregation behavior,
cumulative chemical field, evolutionary computing
process, fitness measure, macroscopic shape,
mathematical function, morphogenic primitives,
self-organizing primitive, shape formation, shape
modeling, structure formation, computational geometry",
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DOI = "doi:10.1109/SMI.2008.4547962",
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abstract = "Motivated by the ability of living cells to form into
specific shapes and structures, we present a new
approach to shape modeling based on self-organizing
primitives whose behaviors are derived via genetic
programming. The key concept of our approach is that
local interactions between the primitives direct them
to come together into a macroscopic shape. The
interactions of the primitives, called morphogenic
primitives (MP), are based on the chemotaxis-driven
aggregation behaviors exhibited by actual living cells.
Here, cells emit a chemical into their environment.
Each cell responds to the stimulus by moving in the
direction of the gradient of the cumulative chemical
field detected at its surface. MPs, though, do not
attempt to completely mimic the behavior of real cells.
The chemical fields are explicitly defined as
mathematical functions and are not necessarily
physically accurate. The explicit mathematical form of
the chemical field functions are derived via genetic
programming (GP), an evolutionary computing process
that evolves a population of functions. A fitness
measure, based on the shape that emerges from the
chemical-field-driven aggregation, determines which
functions will be passed along to later generations.
This paper describes the cell interactions of MPs and
the GP-based method used to define the chemical field
functions needed to produce user- specified shapes from
simple aggregating primitives.",
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notes = "Also known as \cite{4547962}",
- }
Genetic Programming entries for
Linge Bai
Manolya Eyiyurekli
David E Breen
Citations