An Emergent System for Self-Aligning and Self-Organizing Shape Primitives

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@InProceedings{Bai:2008:SASO,

• author = "Linge Bai and Manolya Eyiyurekli and David E. Breen",
• title = "An Emergent System for Self-Aligning and Self-Organizing Shape Primitives",
• booktitle = "Second IEEE International Conference on Self-Adaptive and Self-Organizing Systems, SASO '08",
• year = "2008",
• month = oct,
• pages = "445--454",
• 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",
• DOI = "doi:10.1109/SASO.2008.54",
• 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.",
• notes = "Also known as \cite{4663447}",

}

Genetic Programming entries for Linge Bai Manolya Eyiyurekli David E Breen

Citations