124 research outputs found

    First steps on asynchronous lattice-gas models with an application to a swarming rule

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    International audienceLattice-gas cellular automata are often considered as a particular case of cellular automata in which additional constraints apply, such as conservation of particles or spatial exclusion. But what about their updating? How to deal with non-perfect synchrony? Novel definitions of asynchronism are proposed that respect the specific hypotheses of lattice-gas models. These definitions are then applied to a swarming rule in order to explore the robustness of the global emergent behaviour. In particular, we compare the synchronous and asynchronous case, and remark that anti-alignment of particles is no longer observed when a small critical amount of asynchronism is added

    Is there something like ''modellability'' ? - Reflections on the robustness of discrete models of complex systems

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    International audienceExtended abstract of the talk given in Universidad de Concepcion, Chile, Octobre 21st., 2013. Invitation by Pr. Julio Aracen

    A robustness approach to study metastable behaviours in a lattice-gas model of swarming

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    International audienceResearch in biology is increasingly interested in discrete dynamical systems to simulate natural phenomena with simple models. But how to take into account their robustness? We illustrate this issue by considering the behaviour of a lattice-gas model with an alignment-favouring interaction rule. This model, which has been shown to display a phase transition between an ordered and a disordered phase, follows ergodic dynamics. We present a method based on the study of stability and robustness, and show that the organised phase may result in several different behaviours. We then observe that behaviours are influenced asymptotically by the definition of the cellular lattice

    Spatial competitive games with disingenuously delayed positions

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    Citation: Soltanolkottabi, M., Ben-Arieh, D., & Wu, C.H. (2017). Spatial competitive games with disingenuously delayed positions. Manuscript, Kansas State University, Manhattan, KS.During the last decade, spatial games have received great attention from researchers showing the behavior of populations of players over time in a spatial structure. One of the main factors which can greatly affect the destiny of such populations is the updating scheme used to apprise new strategies of players. Synchronous updating is the most common updating strategy in which all players update their strategy at the same time. In order to be able to describe the behavior of populations more realistically several asynchronous updating schemes have been proposed. Asynchronous game does not use a universal and players can update their strategy at different time steps during the play. In this paper, we introduce a new type of asynchronous strategy updating in which some of the players hide their updated strategy from their neighbors for several time steps. It is shown that this behavior can change the behavior of populations but does not necessarily lead to a higher payoff for the dishonest players. The paper also shows that with dishonest players, the average payoff of players is less than what they think they get, while they are not aware of their neighbors’ true strategy

    Is there a trade-off between simplicity and robustness? Illustration on a lattice-gas model of swarming

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    International audienceWe re-examine a cellular automaton model of swarm formation. The local rule is stochastic and defined simply as a force that aligns particles with their neighbours. This lattice-gas cellular automaton was proposed by Deutsch to mimic the self-organisation process observed in various natural systems (birds, fishes, bacteria, etc.). We explore the various patterns the self-organisation process may adopt. We observe that, according to the values of the two parameters that define the model, the alignment sensitivity and density of particles, the system may display a great variety of patterns. We analyse this surprising diversity of patterns with numerical simulations. We ask where this richness comes from. Is it an intrinsic characteristic of the model or a mere effect of the modelling simplifications

    Asynchronous cellular automata

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    This text has been proposed for the Encyclopedia of Complexity and Systems Science edited by Springer Nature and should appear in 2018.International audienceThis text is intended as an introduction to the topic of asynchronous cellular automata. We start from the simple example of the Game of Life and examine what happens to this model when it is made asynchronous (Sec. 1). We then formulate our definitions and objectives to give a mathematical description of our topic (Sec. 2). Our journey starts with the examination of the shift rule with fully asynchronous updating and from this simple example, we will progressively explore more and more rules and gain insights on the behaviour of the simplest rules (Sec. 3). As we will meet some obstacles in having a full analytical description of the asynchronous behaviour of these rules, we will turn our attention to the descriptions offered by statistical physics, and more specifically to the phase transition phenomena that occur in a wide range of rules (Sec. 4). To finish this journey, we will discuss the various problems linked to the question of asynchrony (Sec. 5) and present some openings for the readers who wish to go further (Sec. 6)

    Probing robustness of cellular automata through variations of asynchronous updating

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    International audienceTypically viewed as a deterministic model of spatial computing, cellular automata are here considered as a collective system subject to the noise inherent to natural computing. The classical updating scheme is replaced by stochastic versions which either randomly update cells or disrupt the cell-to-cell transmission of information. We then use the novel updating schemes to probe the behaviour of Elementary Cellular Automata, and observe a wide variety of results. We study these behaviours in the scope of macroscopic statistical phenomena and microscopic analysis. Finally, we discuss the possibility to use updating schemes to probe the robustness of complex systems

    Physics of Microswimmers - Single Particle Motion and Collective Behavior

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    Locomotion and transport of microorganisms in fluids is an essential aspect of life. Search for food, orientation toward light, spreading of off-spring, and the formation of colonies are only possible due to locomotion. Swimming at the microscale occurs at low Reynolds numbers, where fluid friction and viscosity dominates over inertia. Here, evolution achieved propulsion mechanisms, which overcome and even exploit drag. Prominent propulsion mechanisms are rotating helical flagella, exploited by many bacteria, and snake-like or whip-like motion of eukaryotic flagella, utilized by sperm and algae. For artificial microswimmers, alternative concepts to convert chemical energy or heat into directed motion can be employed, which are potentially more efficient. The dynamics of microswimmers comprises many facets, which are all required to achieve locomotion. In this article, we review the physics of locomotion of biological and synthetic microswimmers, and the collective behavior of their assemblies. Starting from individual microswimmers, we describe the various propulsion mechanism of biological and synthetic systems and address the hydrodynamic aspects of swimming. This comprises synchronization and the concerted beating of flagella and cilia. In addition, the swimming behavior next to surfaces is examined. Finally, collective and cooperate phenomena of various types of isotropic and anisotropic swimmers with and without hydrodynamic interactions are discussed.Comment: 54 pages, 59 figures, review article, Reports of Progress in Physics (to appear

    Common metrics for cellular automata models of complex systems

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    The creation and use of models is critical not only to the scientific process, but also to life in general. Selected features of a system are abstracted into a model that can then be used to gain knowledge of the workings of the observed system and even anticipate its future behaviour. A key feature of the modelling process is the identification of commonality. This allows previous experience of one model to be used in a new or unfamiliar situation. This recognition of commonality between models allows standards to be formed, especially in areas such as measurement. How everyday physical objects are measured is built on an ingrained acceptance of their underlying commonality. Complex systems, often with their layers of interwoven interactions, are harder to model and, therefore, to measure and predict. Indeed, the inability to compute and model a complex system, except at a localised and temporal level, can be seen as one of its defining attributes. The establishing of commonality between complex systems provides the opportunity to find common metrics. This work looks at two dimensional cellular automata, which are widely used as a simple modelling tool for a variety of systems. This has led to a very diverse range of systems using a common modelling environment based on a lattice of cells. This provides a possible common link between systems using cellular automata that could be exploited to find a common metric that provided information on a diverse range of systems. An enhancement of a categorisation of cellular automata model types used for biological studies is proposed and expanded to include other disciplines. The thesis outlines a new metric, the C-Value, created by the author. This metric, based on the connectedness of the active elements on the cellular automata grid, is then tested with three models built to represent three of the four categories of cellular automata model types. The results show that the new C-Value provides a good indicator of the gathering of active cells on a grid into a single, compact cluster and of indicating, when correlated with the mean density of active cells on the lattice, that their distribution is random. This provides a range to define the disordered and ordered state of a grid. The use of the C-Value in a localised context shows potential for identifying patterns of clusters on the grid
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