An Emergent System for Self-Aligning and Self-Organizing Shape Primitives
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @InProceedings{Bai:2008:SASO,
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author = "Linge Bai and Manolya Eyiyurekli and David E. Breen",
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title = "An Emergent System for Self-Aligning and
Self-Organizing Shape Primitives",
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booktitle = "Second IEEE International Conference on Self-Adaptive
and Self-Organizing Systems, SASO '08",
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year = "2008",
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month = oct,
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pages = "445--454",
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keywords = "genetic algorithms, genetic programming, direct
morphogenetic primitives, emergent behavior, emergent
system, evolutionary computing, living cells, local
interaction rules, natural phenomenon, self-aligning
shape primitives, self-organizing shape primitives,
simulation system, user-defined shape, computational
geometry",
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DOI = "doi:10.1109/SASO.2008.54",
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abstract = "Motivated by the natural phenomenon of living cells
self-organizing into specific shapes and structures, we
present an emergent system that uses evolutionary
computing methods for designing and simulating
self-aligning and self-organizing shape
primitives.Given the complexity of the emergent
behavior, genetic programming is employed to control
the evolution of our emergent system. The system has
two levels of description. At the macroscopic level, a
user-specified, pre-defined shape is given as input to
the system. The system outputs local interaction rules
that direct morphogenetic primitives (MP) to aggregate
into the shape. At the microscopic level, MPs follow
interaction rules based only on local interactions. All
MPs are identical and do not know the final shape to be
formed. The aggregate is then evaluated at the
macroscopic level for its similarity to the
user-defined shape. In this paper, we present (1) an
emergent system that discovers local interaction rules
that direct MPs to form user-defined shapes, (2) the
simulation system that implements these rules and
causes MPs to self-align and self-organize into a
user-defined shape, and (3) the robustness and
scalability qualities of the overall approach.",
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notes = "Also known as \cite{4663447}",
- }
Genetic Programming entries for
Linge Bai
Manolya Eyiyurekli
David E Breen
Citations