11,101 research outputs found
Topology based global crowd control
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
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
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
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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