Topic
Continuous automaton
About: Continuous automaton is a research topic. Over the lifetime, 947 publications have been published within this topic receiving 17417 citations.
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TL;DR: It is shown that every random environment discussed up to the present is a special case of this machine and the system consisting of this environment and an automaton is equivalent to an autonomous stochastic automaton.
5 citations
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TL;DR: Two statistically stationary states with power-law scaling of avalanches are found in a simple 1 D cellular automaton and the migration of states of the automaton between these two self-organized criticality states is demonstrated during evolution of the system in computer simulations.
Abstract: Two statistically stationary states with power-law scaling of avalanches are found in a simple 1 D cellular automaton. Features of the fixed points, the spiral saddle and the saddle with index 1, are investigated. The migration of states of the automaton between these two self-organized criticality states is demonstrated during evolution of the system in computer simulations. The automaton, being a slowly driven system, can be applied as a toy model of earthquake supercycles.
5 citations
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TL;DR: This work introduces a novel method for creating behaviors in cellular automata: optimizing the topology of the cellular substrate while maintaining a single simple update rule and provides insights towards the study of morphological computation and embodied cognition.
5 citations
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TL;DR: The adoption of cellular automata introduces a new means of spatial data modelling, in addition to those traditionally provided by GIS packages, resulting in the possibility of storing elements of dynamic knowledge in cellular maps.
5 citations
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TL;DR: When m is very large, the correlations created by the application of the probabilistic cellular automaton rule are destroyed, and, as expected, the behavior of the system is then correctly predicted by a mean-field-type approximation.
Abstract: We study the critical behavior of a probabilistic automata network whose local rule consists of two subrules. The first one, applied synchronously, is a probabilistic one-dimensional range-one cellular automaton rule. The second, applied sequentially, exchanges the values of a pair of sites. According to whether the two sites are first-neighbors or not, the exchange is said to be local or nonlocal. The evolution of the system depends upon two parameters, the probability p characterizing the probabilistic cellular automaton, and the degree of mixing m resulting from the exchange process. Depending upon the values of these parameters, the system exhibits a bifurcation similar to a second order phase transition characterized by a nonnegative order parameter, whose role is played by the stationary density of occupied sites. When m is very large, the correlations created by the application of the probabilistic cellular automaton rule are destroyed, and, as expected, the behavior of the system is then correctly predicted by a mean-field-type approximation. According to whether the exchange of the site values is local or nonlocal, the critical behavior is qualitatively different as m varies.
5 citations