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|CSSS 2006 Santa Fe|
A new type of Cellular Automata is presented and studied: the Neuro-Cellular Automata. The standard way of representing the rules of an automaton is replaced by an Artificial Neural Network. The motivation of this change is two-fold: to have a more biologically inspired automata and to explore the connections between Cellular Automata, Neural Networks, Evolution and Complexity. The process of the development of this kind of automata is also described, as well as some considerations about important aspects of the work. We use simple one-dimensional Cellular Automata, in order to better understand the complexity of the different components of the Neuro-Cellular Automata and to evolve it, because evolution is required to design these type of automata. A study regarding ways to measure complexity is also performed, since these measures play an important role in evaluating the population of automata in the evolutionary process.
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