Biomedical Engineering Reference
In-Depth Information
Modeling Articial Life: A Cellular
Automata Approach
Kunjam Nageswara Rao, Madugula Divya, M. Pallavi
and B. Naga Priyanka
Abstract The key feature of arti
cial life is the idea of emergence, where new
patterns or behaviors emerge from complex computational processes that cannot be
predicted. Emergence initiates the formation of higher-order properties via the
interaction of lower-level properties. Biological networks contain many theory
models of evolution. Similarities between the theoretically estimated networks and
empirically modeled counterpart networks are considered as evidence of the the-
oretic and predictive biological evolution. However, the methods by which these
theoretical models are parameterized and modeled might lead to inference validity
questions. Opting for randomized parametric values is a probabilistic concern that a
model produces. There persists a wide range of probable parameter values which
allow a model to produce varying statistic results according to the parameters
selected. While using the phenomenon of cellular automata, we tried to model life
on a grid of squares. Each square in the grid is taken as a biological cell; we have
framed rules such that the process of cell division and pattern formation in terms of
biological theoretic perspective is studied. Relatively complex behaviors of the cell
patterns which vary from generation to generation are visually analyzed. Three
algorithms
have been imple-
mented whose technical implementation will provide an inspiration and foundation
to build simulators that exhibit characteristics and behaviors of biological systems
of reproduction.
—
game of life, Langton
'
s ant, and hodgepodge
—
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