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Article
Publication date: 1 March 1997

Andrew Adamatzky

To program cellular automata is to define cell neighbourhood and cell‐state transition rules in order to design an automation which exhibits determined patterns in its…

Abstract

To program cellular automata is to define cell neighbourhood and cell‐state transition rules in order to design an automation which exhibits determined patterns in its evolution or which transforms a given image into another image. In general, a tool for the automatic programming of cellular automata should translate the tuple (source‐configuration) → (target‐configuration) into a set of cell‐state transition rules. This is a problem which has not been completely solved yet. Attempts to show examples of automatic programming of cellular automata using identification algorithms. Results obtained can be used in the design of massively parallel processors with cellularautomata architecture and a conventional, as well as non‐traditional (e.g. molecular and chemical), elementary base.

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Kybernetes, vol. 26 no. 2
Type: Research Article
ISSN: 0368-492X

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Article
Publication date: 1 April 2003

Yasser Hassan and Eiichiro Tazaki

It has recently been shown that an approach termed emergence system has gained popularity in a variety of fields, however, emergent computation in decentralized spatially…

Abstract

It has recently been shown that an approach termed emergence system has gained popularity in a variety of fields, however, emergent computation in decentralized spatially extended systems, such as in cellular automata, is still not well understood. To accept that a system is displaying emergent behavior, the system should be constructed by describing local elementary interactions between components. This is achieved in a different way by describing global behavior and properties of the running system over a period of time. This paper introduces the emergent computational paradigm, and discusses its theoretical formulation using a new general model of cellular automata. We have also developed a technique to study the structure of the state transition of cellular automata in the limit of large system size.

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Kybernetes, vol. 32 no. 3
Type: Research Article
ISSN: 0368-492X

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Article
Publication date: 1 July 2006

Yasser Hassan and Eiichiro Tazaki

The aim is identifying and analyzing some well‐defined types of emergence where the paper uses ideas from machine learning and artificial intelligence to provide the model…

Abstract

Purpose

The aim is identifying and analyzing some well‐defined types of emergence where the paper uses ideas from machine learning and artificial intelligence to provide the model of cellular automata based on rough set theory and response in simulated cars.

Design/methodology/approach

This paper proposes, as practical part, a road traffic system based on two‐dimensional cellular automata combined with rough set theory to model the flow and jamming that is suitable to an urban environment.

Findings

The automaton mimics realistic traffic rules that apply in everyday experience.

Research limitations/implications

The modeled development process in this paper involves simulated processes of evolution, learning and self‐organization.

Practical implications

Recently, the examination and modeling of vehicular traffic has become an important subject of research.

Originality/value

The main value of the model is that it provides an illustration of how simple learning processes may lead to the formation of the state machine behavior, which can give an emergent to the model.

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Kybernetes, vol. 35 no. 6
Type: Research Article
ISSN: 0368-492X

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Article
Publication date: 1 April 2003

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108

Abstract

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Kybernetes, vol. 32 no. 3
Type: Research Article
ISSN: 0368-492X

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Article
Publication date: 11 November 2013

Bogdan Bochenek and Katarzyna Tajs-Zielinska

Biologically inspired techniques like cellular automata (CA) are gaining nowadays attention of designers. This is because they are effective, do not require gradient…

Abstract

Purpose

Biologically inspired techniques like cellular automata (CA) are gaining nowadays attention of designers. This is because they are effective, do not require gradient information, and one can easily combine this type of algorithm with any finite element structural analysis code. The purpose of this paper is to develop a CA algorithm based on novel local rules oriented at solving compliance-based topology optimization problems.

Design/methodology/approach

The design domain is divided into lattice of cells, states of which are updated synchronously. The proposed rules include information coming from an individual cell and from its neighborhood, and by introducing weighting parameters allow to control and modify topology generation process.

Findings

The performance of the developed algorithm is very satisfactory, and a comparison with results of other authors, obtained with the use of various optimization techniques, shows efficiency of the present topology generation process. The results found within approach of this paper are in a good agreement with the ones already reported, both for optimal topologies and values of minimal compliance, which in some cases are found even improved.

Practical implications

The algorithm presented in the paper is quite general what allows its easy application to engineering design problems. Moreover, the local update rules are simple, so they can be easily implemented into professional FEM analysis codes, as an efficient add-on module for topology optimization.

Originality/value

The main advantage of the developed algorithm is that it is a fast convergent technique and usually requires far less iterations as to achieve the solution, when compared to other approaches. What is also important does not require any additional density filtering. It also overcomes some drawbacks of traditional approaches so that changing mesh density does not influence resulting topologies and solutions are free from checkerboard effect.

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Engineering Computations, vol. 30 no. 8
Type: Research Article
ISSN: 0264-4401

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Book part
Publication date: 17 October 2014

Philip Z. Maymin

Economic models based on simple rules can result in complex and unpredictable deterministic dynamics with emergent features similar to those of actual economies. I present…

Abstract

Economic models based on simple rules can result in complex and unpredictable deterministic dynamics with emergent features similar to those of actual economies. I present several such models ranging from cellular automaton and register machines to quantum computation. The additional benefit of such models is displayed by extending them to model political entanglement to determine the impact of allowing majority redistributive voting. In general, the insights obtained from simulating the computations of simple rules can serve as an additional way to study economics, complementing equilibrium, literary, experimental, and empirical approaches. I culminate by presenting a minimal model of economic complexity that generates complex economic growth and diminishing poverty without any parameter fitting, and which, when modified to incorporate political entanglement, generates volatile stagnation and greater poverty.

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Entangled Political Economy
Type: Book
ISBN: 978-1-78441-102-2

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Article
Publication date: 1 November 1997

A. Berezovski

Describes an extension of cellular automata to simulate heat conduction process. The offered algorithms is rather the tool for the direct simulation of a process than for…

Abstract

Describes an extension of cellular automata to simulate heat conduction process. The offered algorithms is rather the tool for the direct simulation of a process than for the solution of partial differential equations. Its essential feature is the absence of any partial differential equations used widely for the description of heat conduction. Moreover, Fourier’s law (or any of its generalizations) is not even used. Instead, the equations of state for a medium are applied immediately together with a rule of updating of cell’s states which follows from thermodynamic laws applied to interacting systems. The interaction is described in terms of Gibbsian state space. One‐dimensional heat conduction in a stationary layer is considered as an example. Shows that steady‐state temperature distributions are linear in the case of solids in full correspondence with the classical theory. At the same time, these distributions are significantly non‐linear in water, especially under sufficiently large gravitational force or in regions of phase transitions.

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International Journal of Numerical Methods for Heat & Fluid Flow, vol. 7 no. 7
Type: Research Article
ISSN: 0961-5539

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Article
Publication date: 7 November 2016

Joan C. Micó, Antonio Caselles, David Soler and Pantaleón D. Romero

The purpose of this paper is to suggest a formalism given by an equation suitable for simulating discrete systems with space-time variation in addition to other change…

Abstract

Purpose

The purpose of this paper is to suggest a formalism given by an equation suitable for simulating discrete systems with space-time variation in addition to other change variables. With such formalism, multidimensional dynamical models of discrete complex systems, such as the social systems and ecosystems, can be built.

Design/methodology/approach

This formalism is named as discrete multidimensional dynamic system (DMDS). The DMDS provides a way to consider the variation of the density of a state variable with regard to the variables of the change space as a function of multidimensional rates. Multidimensional rates describe this evolution as a consequence of the relation of each multidimensional-point with a given set of other points of the change space. This relation contains the accessibility domains (sets of space points with which each space point is related).

Findings

This equation is compared with both the reaction-diffusion equation written in its finite difference form and the cellular-automata model, demonstrating its compatibility with them and an increase in generality, widening the scope of application. The steps to construct models of systems with multidimensional variation based on the equation that defines the DMDS are specified and tested.

Research limitations/implications

Through the DMDS and a well-stated methodology, an application case is provided in order to describe the multidimensional demographic dynamics of an urban system. In this case, the numerical evolution of the population density by districts and cohorts is determined by the DMDS based on some hypothesis about functions of population diffusion between the different districts of the system.

Originality/value

The scope of application of the space-time dynamic system (STDS), given by the authors in a previous work, has been extended to discrete and multidimensional systems. STDS model produces better results than the reaction-diffusion model in validation.

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Kybernetes, vol. 45 no. 10
Type: Research Article
ISSN: 0368-492X

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Article
Publication date: 27 April 2012

Carlos Gershenson and David A. Rosenblueth

The purpose of this paper is to compare qualitatively two methods for coordinating traffic lights: a static optimization “green wave” method and an adaptive self‐organizing method.

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Abstract

Purpose

The purpose of this paper is to compare qualitatively two methods for coordinating traffic lights: a static optimization “green wave” method and an adaptive self‐organizing method.

Design/methodology/approach

Statistical results were obtained from implementing a recently proposed model of city traffic based on elementary cellular automata in a computer simulation.

Findings

The self‐organizing method delivers considerable improvements over the green‐wave method. Seven dynamical regimes and six phase transitions are identified and analyzed for the self‐organizing method.

Practical implications

The paper shows that traffic light coordination can be improved in cities by using self‐organizing methods.

Social implications

This improvement can have a noticeable effect on the quality of life of citizens.

Originality/value

Understanding how self‐organization obtains adaptive solutions for complex problems can contribute to building more efficient systems.

Details

Kybernetes, vol. 41 no. 3/4
Type: Research Article
ISSN: 0368-492X

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Book part
Publication date: 5 November 2021

Andrew Pilny

This chapter conceptualizes computational methods across three related, yet distinct approaches: (1) Social Simulation, (2) Data Science, and (3) Big Data. Group…

Abstract

This chapter conceptualizes computational methods across three related, yet distinct approaches: (1) Social Simulation, (2) Data Science, and (3) Big Data. Group communication research is then situated and reviewed along these three lines of research. Although some areas have considerable visibility (e.g., network analysis, text mining), some areas are less visible in group communication research (e.g., Social Simulation, Big Data designs). The chapter concludes with suggestions for issues regarding reliability, validity, and ethics.

Details

The Emerald Handbook of Group and Team Communication Research
Type: Book
ISBN: 978-1-80043-501-8

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