Team/CINVESTAV-IPN-UNAM MX/automata.htm

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         At this point, the program runs  simulations based on precompiled transition rules, but due to the inherent  complexity of cellular automata, a single simulation isn´t enough. So the next  step is to vary the concentrations and apply an evolutionary algorithm to  modify the starting conditions of the &quot;game&quot; in each iteration cycle.</p>
         At this point, the program runs  simulations based on precompiled transition rules, but due to the inherent  complexity of cellular automata, a single simulation isn´t enough. So the next  step is to vary the concentrations and apply an evolutionary algorithm to  modify the starting conditions of the &quot;game&quot; in each iteration cycle.</p>
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<p><strong>Figure 1.  TWO-DIMENSIONAL CELLULAR AUTOMATA.</strong></p>
<p><strong>Figure 1.  TWO-DIMENSIONAL CELLULAR AUTOMATA.</strong></p>
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Revision as of 01:06, 27 September 2012

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Cellular automata approaches to biological modeling.


In the near future, our project can be used to produce biofuels, so we decided to create a software that allows us to generate Pilot-Plant simulations. 


To perform this software, we are taking the  two-dimensional Cellular Automata developed  by  John Conway called "GAME OF LIFE", and  extending it over a living cell type, in where there are several stages of the cell and different scope ranges. Our goal is to generate enough simulations at different concentrations of reactants or products under distinct environmental conditions; until the program shows what inputs (concentrations) are optimal to maximize the production.


At this point, the program runs simulations based on precompiled transition rules, but due to the inherent complexity of cellular automata, a single simulation isn´t enough. So the next step is to vary the concentrations and apply an evolutionary algorithm to modify the starting conditions of the "game" in each iteration cycle.

Figure 1.  TWO-DIMENSIONAL CELLULAR AUTOMATA.