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Reconnaissance de langage en temps réel sur automates cellulaires 2D

Abstract : Cellular automata were introduced in the 50s by J. von Neumann and S. Ulamas an efficient way of modeling massively parallel computation. Many variations of the model can be considered such as varying the dimension of the computation space or the communication capabilities of the computing cells. In a cellular automaton each cell can communicate only with a finite number of other cells called its neighbors. My work focuses on the impact of the choice of the neighbors on the algorithmic properties of the model. My first goal was to generalize some classical properties of computation models to the widest possible class of neighborhoods, in particular I prove a linear speedup theorem for any two dimensional neighborhood. I then study the difference between the complexity classes defined by different neighborhoods, show the existence of neighborhoods defining incomparable classes, and some sets of neighborhoods defining identical classes. Finally, I also discuss the impact of the dimension of the automata on their computational power.
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Submitted on : Friday, June 15, 2018 - 10:13:04 PM
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Anaël Grandjean. Reconnaissance de langage en temps réel sur automates cellulaires 2D. Autre [cs.OH]. Université Montpellier, 2016. Français. ⟨NNT : 2016MONTT331⟩. ⟨tel-01816961⟩



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