Computer Simulation of Dialect Feature Diffusion

2014 ◽  
Vol 2 (1) ◽  
pp. 41-57 ◽  
Author(s):  
William A. Kretzschmar ◽  
Ilkka Juuso ◽  
C. Thomas Bailey

This paper describes the independent construction and implementation of two cellular automata that model dialect feature diffusion as the adaptive aspect of the complex system of speech. We show how a feature, once established, can spread across an area, and how the distribution of a dialect feature as it stands in Linguistic Atlas data could either spread or diminish. Cellular automata use update rules to determine the status of a feature at a given location with respect to the status of its neighboring locations. In each iteration all locations in a matrix are evaluated, and then the new status for each one is displayed all at once. Throughout hundreds of iterations, we can watch regional distributional patterns emerge as a consequence of these simple update rules. We validate patterns with respect to the linguistic distributions known to occur in the Linguistic Atlas Project.

Author(s):  
Terry Bossomaier

In this chapter we present a view of cellular automata (CAs) as the quintessential complex system and how they can be used for complex systems modelling. First we consider theoretical issues of the complexity of their behaviour, discussing the Wolfram Classification, the Langton, lambda parameter and the edge of chaos. Then we consider the input entropy as a way of quantifying complex rules. Finally we contrast explicit CA modelling of geophysical systems with heuristic particle based methods for the visualisation of lava flows.


2008 ◽  
Vol 575-578 ◽  
pp. 109-114
Author(s):  
Liang Yu ◽  
Liu Shun Wu ◽  
Liao Sha Li ◽  
Yuan Chi Dong

Dendrite structure in solidification process has been studied by many researchers for it’s widely existence. In present work, a cellular automata model was proposed according to the basic physical chemistry concepts, which was helpful for a better understanding of the dendrite crystal growth and its physical chemistry mechanism. Two kinds of structures were considered in the model: hexagonal and rectangle. The status of every site was set as 0 and 1 which represent non-solidified and solidified state. Temperature field was simulated using finite difference method on the same mesh. The states of sites were changed according to the overcooling condition only. The computer simulation results showed that dendrite structure could be obtained under overcooling condition and temperature field calculation only, the structure of the dendrite was decided by the geometry of the model. The simulation resulted similar pattern as that obtained by experimental observation. The present model suggested that there exist a very simple basic for the typical complex phenomena, dendrite structure.


2008 ◽  
Vol 18 (02) ◽  
pp. 527-539 ◽  
Author(s):  
RAMÓN ALONSO-SANZ ◽  
ANDREW ADAMATZKY

Commonly studied cellular automata are memoryless and have fixed topology of connections between cells. However by allowing updates of links and short-term memory in cells we may potentially discover novel complex regimes of spatio-temporal dynamics. Moreover, by adding memory and dynamical topology to state update rules we somehow forge elementary but nontraditional models of neurons networks (aka neuron layers in frontal parts). In the present paper, we demonstrate how this can be done on a self-inhibitory excitable cellular automata. These automata imitate a phenomenon of inhibition caused by hight-strength stimulus: a resting cell excites if there are one or two excited neighbors, the cell remains resting otherwise. We modify the automaton by allowing cells to have few-steps memories, and create links between neighboring cells removed or generated depending on the states of the cells.


Complexity ◽  
2008 ◽  
Vol 13 (6) ◽  
pp. 21-28 ◽  
Author(s):  
Fabio Boschetti ◽  
David McDonald ◽  
Randall Gray

2018 ◽  
Vol 7 (2.23) ◽  
pp. 1
Author(s):  
Aleksey Gavrilin ◽  
Tatiana Gorbunova ◽  
Marina Tumanova ◽  
Oleg Ratnikov

Relevance of the present task lays in optimization of control over complex systems considering probabilistic and temporal nature of their functioning. Allocated some generic States of the system's normal operation and consider destabilizing situations when the continued functioning of the element in the system becomes difficult, impossible. Including the status when it is necessary to conduct full diagnostic and restoring of the system with explicit damage which makes it impossible for the system to operate in the acceptable mode into the model is described in the work. The proposed solution to this task is based on the mathematical modelling. Considering the general case of nonexponential time of system residence in its own status, the proposed functioning model displays relations between system statuses and probable parameters of its functioning on the base of semi-Markov process theory. Because of this work the explanation of an adequate description of complex system functioning at probabilistic and temporal analysis was presented.  


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