A universal non-conservative reversible elementary triangular partitioned cellular automaton that shows complex behavior

2017 ◽  
Vol 18 (3) ◽  
pp. 413-428 ◽  
Author(s):  
Kenichi Morita
Keyword(s):  
Cellular Automaton ◽  
Complex Behavior

Cellular Automaton Simulation of Polymers

1991 ◽  
Vol 248 ◽  
Author(s):  
M. A. Smith ◽  
Y. Bar-Yam ◽  
Y. Rabin ◽  
N. Margolus ◽  
T. Toffoli ◽  
...  
Keyword(s):  
Parallel Processing ◽  
Cellular Automata ◽  
Cellular Automaton ◽  
Large Scale ◽  
Dynamic Properties ◽  
Two Dimensions ◽  
Excluded Volume ◽  
Complex Behavior ◽  
Dynamical Models ◽  
Space Partitioning

AbstractIn order to improve our ability to simulate the complex behavior of polymers, we introduce dynamical models in the class of Cellular Automata (CA). Space partitioning methods enable us to overcome fundamental obstacles to large scale simulation of connected chains with excluded volume by parallel processing computers. A highly efficient, two-space algorithm is devised and tested on both Cellular Automata Machines (CAMs) and serial computers. Preliminary results on the static and dynamic properties of polymers in two dimensions are reported.

Cellular Automata Metrics

2010 ◽  
pp. 114-149
Author(s):  
Eleonora Bilotta ◽  
Pietro Pantano
Keyword(s):  
Complex System ◽  
Cellular Automata ◽  
Cellular Automaton ◽  
Initial Conditions ◽  
Biological Systems ◽  
Complexity Science ◽  
Complex Behavior ◽  
Multiple Components ◽  
Complex Phenomena

There have been many attempts to understand complexity and to represent it in terms of computable quantities. To date, however, these attempts have had little success. Although we find complexity in a broad range of scientific domains, precise definitions escape our grasp (Bak, 1996; Morin, 2001; Prigogine & Stengers, 1984). One of the key models in complexity science is the Cellular Automaton (CA), a class of system in which small changes in the initial conditions or in local rules can provoke unpredictable behavior (Wolfram, 1984; Wolfram, 2002; Langton, 1986; 1990). The key issue, here as in other kinds of complex system, is to discover the rules governing the emergence of complex phenomena. If such rules were known we could use them to model and predict the behavior of complex physical and biological systems. Taking it for granted that complex behavior is the result of interactions among multiple components of a larger system; we can ask a number of fundamental questions.

A Probabilistic Cellular Automaton for Evolution

1995 ◽  
Vol 5 (9) ◽  
pp. 1129-1134 ◽  
Author(s):  
Nikolaus Rajewsky ◽  
Michael Schreckenberg
Keyword(s):  
Cellular Automaton ◽  
Probabilistic Cellular Automaton

Autómatas Celulares Aplicados al Comportamiento de Células de Cáncer Cervicouterino

2019 ◽  
Vol 6 (1) ◽  
pp. 44-49
Author(s):  
Tania Muñoz Jiménez ◽  
Aurora Torres Soto ◽  
María Dolores Torres Soto
Keyword(s):  
Cellular Automaton ◽  
Medical Model ◽  
Research Process ◽  
Simulation Algorithm ◽  
Stages Of Development ◽  
Literary Research ◽  
Migration Dynamics ◽  
Three Stages ◽  
And Migration ◽  
Best Parameters

En este documento se describe el desarrollo e implementación de un modelo para simular computacionalmente la dinámica del crecimiento y migración del cáncer cervicouterino, considerando sus principales características: proliferación, migración y necrosis, así como sus etapas de desarrollo. El modelo se desarrolló mediante un autómata celular con enfoques paralelo y secuencial. El autómata celular se basó en el modelo de Gompertz para simular las etapas de desarrollo de este cáncer, el cual se dividió en tres etapas cada una con diferentes comportamientos durante la simulación. Se realizó un diseño experimental con parámetros de entrada que se seleccionaron a partir de la investigación literaria y su discusión con médicos expertos. Al final del proceso de investigación, se logró obtener un algoritmo computacional de simulación muy bueno comparado con el modelo médico de Gompertz y se encontraron los mejores parámetros para su ejecución mediante un diseño factorial soportado estadísticamente. This paper describes the development and implementation of a model to computationally simulate the growth and migration dynamics of cervical cancer, considering its main characteristics: proliferation, migration and necrosis, as well as its stages of development. The model was developed by means of a cellular automaton with parallel and sequential approaches. The cellular automaton was based on the model of Gompertz to simulate the stages of development of this cancer, which was divided into three stages, each with different behaviors during the simulation. An experimental design was carried out with input parameters that were selected from literary research and its discussion with expert physicians. At the end of the research process, a very good simulation algorithm was obtained compared to the Gompertz medical model and the best parameters for its execution were found by means of a statistically supported factorial design.

Replication of a Binary Image on a One-Dimensional Cellular Automaton with Linear Rules

2018 ◽  
Vol 27 (4) ◽  
pp. 415-430
Author(s):  
U Srinivasa Rao ◽  
Jeganathan L ◽  
Keyword(s):  
Cellular Automaton ◽  
Binary Image ◽  
One Dimensional

Simulating Self-Regeneration and Self-Replication Processes Using Movable Cellular Automata with a Mutual Equilibrium Neighborhood

2020 ◽  
Vol 29 (4) ◽  
pp. 741-757
Author(s):  
Kateryna Hazdiuk ◽  
◽  
Volodymyr Zhikharevich ◽  
Serhiy Ostapov ◽  
◽  
...  
Keyword(s):  
Cellular Automata ◽  
Cellular Automaton ◽  
Three Dimensional ◽  
Computer Models ◽  
The Self ◽  
Model Construction ◽  
Natural Phenomena ◽  
Different Types ◽  
Movable Cellular Automata ◽  
Self Replication

This paper deals with the issue of model construction of the self-regeneration and self-replication processes using movable cellular automata (MCAs). The rules of cellular automaton (CA) interactions are found according to the concept of equilibrium neighborhood. The method is implemented by establishing these rules between different types of cellular automata (CAs). Several models for two- and three-dimensional cases are described, which depict both stable and unstable structures. As a result, computer models imitating such natural phenomena as self-replication and self-regeneration are obtained and graphically presented.

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