11,101 research outputs found

    Topology based global crowd control

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    We propose a method to determine the flow of large crowds of agents in a scene such that it is filled to its capacity with a coordinated, dynamically moving crowd. Our approach provides a focus on cooperative control across the entire crowd. This is done with a view to providing a method which animators can use to easily populate and fill a scene. We solve this global planning problem by first finding the topology of the scene using a Reeb graph, which is computed from a Harmonic field of the environment. The Maximum flow can then be calculated across this graph detailing how the agents should move through the space. This information is converted back from the topological level to the geometric using a route planner and the Harmonic field. We provide evidence of the system’s effectiveness in creating dynamic motion through comparison to a recent method. We also demonstrate how this system allows the crowd to be controlled globally with a couple of simple intuitive controls and how it can be useful for the purpose of designing buildings and providing control in team sports

    How to suppress undesired synchronization

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    It is delightful to observe the emergence of synchronization in the blinking of fireflies to attract partners and preys. Other charming examples of synchronization can also be found in a wide range of phenomena such as, e.g., neurons firing, lasers cascades, chemical reactions, and opinion formation. However, in many situations the formation of a coherent state is not pleasant and should be mitigated. For example, the onset of synchronization can be the root of epileptic seizures, traffic congestion in communication networks, and the collapse of constructions. Here we propose the use of contrarians to suppress undesired synchronization. We perform a comparative study of different strategies, either requiring local or total knowledge of the system, and show that the most efficient one solely requires local information. Our results also reveal that, even when the distribution of neighboring interactions is narrow, significant improvement in mitigation is observed when contrarians sit at the highly connected elements. The same qualitative results are obtained for artificially generated networks as well as two real ones, namely, the Routers of the Internet and a neuronal network

    Visualizing Sensor Network Coverage with Location Uncertainty

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    We present an interactive visualization system for exploring the coverage in sensor networks with uncertain sensor locations. We consider a simple case of uncertainty where the location of each sensor is confined to a discrete number of points sampled uniformly at random from a region with a fixed radius. Employing techniques from topological data analysis, we model and visualize network coverage by quantifying the uncertainty defined on its simplicial complex representations. We demonstrate the capabilities and effectiveness of our tool via the exploration of randomly distributed sensor networks

    Minority Game With Peer Pressure

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    To study the interplay between global market choice and local peer pressure, we construct a minority-game-like econophysical model. In this so-called networked minority game model, every selfish player uses both the historical minority choice of the population and the historical choice of one's neighbors in an unbiased manner to make decision. Results of numerical simulation show that the level of cooperation in the networked minority game differs remarkably from the original minority game as well as the prediction of the crowd-anticrowd theory. We argue that the deviation from the crowd-anticrowd theory is due to the negligence of the effect of a four point correlation function in the effective Hamiltonian of the system.Comment: 10 pages, 3 figures in revtex 4.
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