4,238 research outputs found

    Cellular Automata Applications in Shortest Path Problem

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    Cellular Automata (CAs) are computational models that can capture the essential features of systems in which global behavior emerges from the collective effect of simple components, which interact locally. During the last decades, CAs have been extensively used for mimicking several natural processes and systems to find fine solutions in many complex hard to solve computer science and engineering problems. Among them, the shortest path problem is one of the most pronounced and highly studied problems that scientists have been trying to tackle by using a plethora of methodologies and even unconventional approaches. The proposed solutions are mainly justified by their ability to provide a correct solution in a better time complexity than the renowned Dijkstra's algorithm. Although there is a wide variety regarding the algorithmic complexity of the algorithms suggested, spanning from simplistic graph traversal algorithms to complex nature inspired and bio-mimicking algorithms, in this chapter we focus on the successful application of CAs to shortest path problem as found in various diverse disciplines like computer science, swarm robotics, computer networks, decision science and biomimicking of biological organisms' behaviour. In particular, an introduction on the first CA-based algorithm tackling the shortest path problem is provided in detail. After the short presentation of shortest path algorithms arriving from the relaxization of the CAs principles, the application of the CA-based shortest path definition on the coordinated motion of swarm robotics is also introduced. Moreover, the CA based application of shortest path finding in computer networks is presented in brief. Finally, a CA that models exactly the behavior of a biological organism, namely the Physarum's behavior, finding the minimum-length path between two points in a labyrinth is given.Comment: To appear in the book: Adamatzky, A (Ed.) Shortest path solvers. From software to wetware. Springer, 201

    Nature-Inspired Interconnects for Self-Assembled Large-Scale Network-on-Chip Designs

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    Future nano-scale electronics built up from an Avogadro number of components needs efficient, highly scalable, and robust means of communication in order to be competitive with traditional silicon approaches. In recent years, the Networks-on-Chip (NoC) paradigm emerged as a promising solution to interconnect challenges in silicon-based electronics. Current NoC architectures are either highly regular or fully customized, both of which represent implausible assumptions for emerging bottom-up self-assembled molecular electronics that are generally assumed to have a high degree of irregularity and imperfection. Here, we pragmatically and experimentally investigate important design trade-offs and properties of an irregular, abstract, yet physically plausible 3D small-world interconnect fabric that is inspired by modern network-on-chip paradigms. We vary the framework's key parameters, such as the connectivity, the number of switch nodes, the distribution of long- versus short-range connections, and measure the network's relevant communication characteristics. We further explore the robustness against link failures and the ability and efficiency to solve a simple toy problem, the synchronization task. The results confirm that (1) computation in irregular assemblies is a promising and disruptive computing paradigm for self-assembled nano-scale electronics and (2) that 3D small-world interconnect fabrics with a power-law decaying distribution of shortcut lengths are physically plausible and have major advantages over local 2D and 3D regular topologies

    Multi-agent simulation: new approaches to exploring space-time dynamics in GIS

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    As part of the long term quest to develop more disaggregate, temporally dynamic models of spatial behaviour, micro-simulation has evolved to the point where the actions of many individuals can be computed. These multi-agent systems/simulation(MAS) models are a consequence of much better micro data, more powerful and user-friendly computer environments often based on parallel processing, and the generally recognised need in spatial science for modelling temporal process. In this paper, we develop a series of multi-agent models which operate in cellular space.These demonstrate the well-known principle that local action can give rise to global pattern but also how such pattern emerges as the consequence of positive feedback and learned behaviour. We first summarise the way cellular representation is important in adding new process functionality to GIS, and the way this is effected through ideas from cellular automata (CA) modelling. We then outline the key ideas of multi-agent simulation and this sets the scene for three applications to problems involving the use of agents to explore geographic space. We first illustrate how agents can be programmed to search route networks, finding shortest routes in adhoc as well as structured ways equivalent to the operation of the Bellman-Dijkstra algorithm. We then demonstrate how the agent-based approach can be used to simulate the dynamics of water flow, implying that such models can be used to effectively model the evolution of river systems. Finally we show how agents can detect the geometric properties of space, generating powerful results that are notpossible using conventional geometry, and we illustrate these ideas by computing the visual fields or isovists associated with different viewpoints within the Tate Gallery.Our forays into MAS are all based on developing reactive agent models with minimal interaction and we conclude with suggestions for how these models might incorporate cognition, planning, and stronger positive feedbacks between agents

    The Effect of Integrating Travel Time

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    This contribution demonstrates the potential gain for the quality of results in a simulation of pedestrians when estimated remaining travel time is considered as a determining factor for the movement of simulated pedestrians. This is done twice: once for a force-based model and once for a cellular automata-based model. The results show that for the (degree of realism of) simulation results it is more relevant if estimated remaining travel time is considered or not than which modeling technique is chosen -- here force-based vs. cellular automata -- which normally is considered to be the most basic choice of modeling approach.Comment: preprint of Pedestrian and Evacuation 2012 conference (PED2012) contributio

    Quickest Paths in Simulations of Pedestrians

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    This contribution proposes a method to make agents in a microscopic simulation of pedestrian traffic walk approximately along a path of estimated minimal remaining travel time to their destination. Usually models of pedestrian dynamics are (implicitly) built on the assumption that pedestrians walk along the shortest path. Model elements formulated to make pedestrians locally avoid collisions and intrusion into personal space do not produce motion on quickest paths. Therefore a special model element is needed, if one wants to model and simulate pedestrians for whom travel time matters most (e.g. travelers in a station hall who are late for a train). Here such a model element is proposed, discussed and used within the Social Force Model.Comment: revised version submitte

    Пошук найкоротшого шляху на графі за допомогою клітинних автоматів

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    Актуальність теми. Визначення оптимального маршруту між об’єктами може здійснюватися в статичному, динамічному режимах і режимах реального часу. Це питання розглядається в багатьох важливих програмах у сфері GPS, відеоігор, робототехніки, логістики та симуляції натовпу - часові середовища. Проблема пошуку шляху може мати багато різних форм, включаючи ті, що стосуються одного агенту, групи агентів, конкурентного пошуку, динамічних змін навколишнього середовища, неоднорідної місцевості, мобільних пристроїв і неповна інформація. Алгоритм пошуку шляху та створення графіка для його реалізації є двома основними компонентами пошуку рушення проблеми. Метою роботи є розробка програмного забезпечення, яке може вирішити проблему пошуку найкоротшого шляху на графі за допомогою клітинних автоматів. Завдання дослідження: - Проаналізувати існуючі програмні застосунки, що досліджують алгоритми пошуку шляху за допомогою клітинних автоматів - Встановити набір правил для генерації клітинного автомату, що дозволяє моделювати пошук найкоротшого шляху на графі - Реалізувати програмний продукт для дослідження використання клітинних автоматів для пошуку шляху на графі на основі встановлених правил Об’єктом дослідження є динамічні системи. Предмет дослідження є клітинні автомати. Методи дослідження. При дослідженнях використовується методики порівняння, абстрагування та аналізу, динамічних систем, прикладної геометрії, комп’ютерної графіки.Actuality of theme. Determination of the optimal route between objects can be carried out in static, dynamic and real-time modes. This issue is addressed in many important applications in the fields of GPS, video games, robotics, logistics, and crowd simulation - temporal environments. The pathfinding problem can take many different forms, including those involving a single agent, a group of agents, competitive search, dynamic environmental changes, heterogeneous terrain, mobile devices, and incomplete information. A path finding algorithm and creating a graph for its implementation are the two main components of finding a solution to a problem. The goal of the work is to develop software that can solve the problem of finding the shortest path on a graph using cellular automata. Objectives of the study: - To analyze the existing software applications that investigate the algorithms of finding a path with the help of cellular automata - Establish a set of rules for the generation of a cellular automaton, which allows simulating the search for the shortest path on a graph - Implement a software product to research the use of cellular automata for graph pathfinding based on established rules The object of research is dynamic systems. The subject of research is cellular automata. Research methods. The research uses methods of comparison, abstraction and analysis, dynamic systems, applied geometry, and computer graphics
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