Pedestrian Group Behavior in a Cellular Automaton

Author(s):  
Michael Seitz ◽  
Gerta Köster ◽  
Alexander Pfaffinger
2021 ◽  
Vol 5 (4) ◽  
pp. 42-48
Author(s):  
Valerii Chystov ◽  
Iryna Zakharchenko ◽  
Vladislava Pavlenko ◽  
Maksim Pavlenko

Currently, a large number of different mathematical models and methods aimed at solving problems of multidimensional optimization and modeling of complex behavioral systems have been developed. One of the areas of search for solutions is the search for solutions in conditions of incomplete information and the need to take into account changing external factors. Often such problems are solved by the method of complete search. In some conditions, the method of complete search can be significantly improved through the implementation and use of behavioral models of natural formations. Examples of such formations can be group behavior of insects, birds, fish, various flocks, etc. The idea of copying group activity of a shoal of fishes at the decision of problems of joint activity on extraction of food is used in work. The reasoning based on the simulation of the behavior of such a natural object allowed to justify the choice as a mathematical model - cellular automata. The paper examines the key features of such a model. Modeling of his work is carried out, strategies of behavior of group of mobile objects at search of the purposes are developed, key characteristics are investigated and the method of adaptive choice of strategy and change of rules of behavior taking into account features of the solved problem is developed. The search strategy is implemented in the work, which takes into account the need to solve the optimization problem on two parameters. The obtained results testify to the high descriptive possibility of such an approach, the possibility of finding the optimal strategy for the behavior of the cellular automaton and the formalization of the process of selecting the parameters of its operation. A further improvement of this approach can be the implementation of simulation to study the properties of the developed model, the formation of the optimal set of rules and parameters of the machine for the whole set of tasks.


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

2019 ◽  
Vol 6 (1) ◽  
pp. 44-49
Author(s):  
Tania Muñoz Jiménez ◽  
Aurora Torres Soto ◽  
María Dolores Torres Soto

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.


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