14,630 research outputs found
A macroscopic analytical model of collaboration in distributed robotic systems
In this article, we present a macroscopic analytical model of collaboration in a group of reactive robots. The model consists of a series of coupled differential equations that describe the dynamics of group behavior. After presenting the general model, we analyze in detail a case study of collaboration, the stick-pulling experiment, studied experimentally and in simulation by Ijspeert et al. [Autonomous Robots, 11, 149-171]. The robots' task is to pull sticks out of their holes, and it can be successfully achieved only through the collaboration of two robots. There is no explicit communication or coordination between the robots. Unlike microscopic simulations (sensor-based or using a probabilistic numerical model), in which computational time scales with the robot group size, the macroscopic model is computationally efficient, because its solutions are independent of robot group size. Analysis reproduces several qualitative conclusions of Ijspeert et al.: namely, the different dynamical regimes for different values of the ratio of robots to sticks, the existence of optimal control parameters that maximize system performance as a function of group size, and the transition from superlinear to sublinear performance as the number of robots is increased
Artificial intelligence in the cyber domain: Offense and defense
Artificial intelligence techniques have grown rapidly in recent years, and their applications in practice can be seen in many fields, ranging from facial recognition to image analysis. In the cybersecurity domain, AI-based techniques can provide better cyber defense tools and help adversaries improve methods of attack. However, malicious actors are aware of the new prospects too and will probably attempt to use them for nefarious purposes. This survey paper aims at providing an overview of how artificial intelligence can be used in the context of cybersecurity in both offense and defense.Web of Science123art. no. 41
Spatially hybrid computations for streamer discharges with generic features of pulled fronts: I. Planar fronts
Streamers are the first stage of sparks and lightning; they grow due to a
strongly enhanced electric field at their tips; this field is created by a thin
curved space charge layer. These multiple scales are already challenging when
the electrons are approximated by densities. However, electron density
fluctuations in the leading edge of the front and non-thermal stretched tails
of the electron energy distribution (as a cause of X-ray emissions) require a
particle model to follow the electron motion. As super-particle methods create
wrong statistics and numerical artifacts, modeling the individual electron
dynamics in streamers is limited to early stages where the total electron
number still is limited.
The method of choice is a hybrid computation in space where individual
electrons are followed in the region of high electric field and low density
while the bulk of the electrons is approximated by densities (or fluids). We
here develop the hybrid coupling for planar fronts. First, to obtain a
consistent flux at the interface between particle and fluid model in the hybrid
computation, the widely used classical fluid model is replaced by an extended
fluid model. Then the coupling algorithm and the numerical implementation of
the spatially hybrid model are presented in detail, in particular, the position
of the model interface and the construction of the buffer region. The method
carries generic features of pulled fronts that can be applied to similar
problems like large deviations in the leading edge of population fronts etc.Comment: 33 pages, 15 figures and 2 table
Long-range Acoustic Interactions in Insect Swarms: An Adaptive Gravity Model
The collective motion of groups of animals emerges from the net effect of the
interactions between individual members of the group. In many cases, such as
birds, fish, or ungulates, these interactions are mediated by sensory stimuli
that predominantly arise from nearby neighbors. But not all stimuli in animal
groups are short range. Here, we consider mating swarms of midges, which
interact primarily via long-range acoustic stimuli. We exploit the similarity
in form between the decay of acoustic and gravitational sources to build a
model for swarm behavior. By accounting for the adaptive nature of the midges'
acoustic sensing, we show that our "adaptive gravity" model makes mean-field
predictions that agree well with experimental observations of laboratory
swarms. Our results highlight the role of sensory mechanisms and interaction
range in collective animal behavior. The adaptive interactions that we present
here open a new class of equations of motion, which may appear in other
biological contexts.Comment: 25 pages, 15 figure
Analyzing and Modeling Special Offer Campaigns in Location-based Social Networks
The proliferation of mobile handheld devices in combination with the
technological advancements in mobile computing has led to a number of
innovative services that make use of the location information available on such
devices. Traditional yellow pages websites have now moved to mobile platforms,
giving the opportunity to local businesses and potential, near-by, customers to
connect. These platforms can offer an affordable advertisement channel to local
businesses. One of the mechanisms offered by location-based social networks
(LBSNs) allows businesses to provide special offers to their customers that
connect through the platform. We collect a large time-series dataset from
approximately 14 million venues on Foursquare and analyze the performance of
such campaigns using randomization techniques and (non-parametric) hypothesis
testing with statistical bootstrapping. Our main finding indicates that this
type of promotions are not as effective as anecdote success stories might
suggest. Finally, we design classifiers by extracting three different types of
features that are able to provide an educated decision on whether a special
offer campaign for a local business will succeed or not both in short and long
term.Comment: in The 9th International AAAI Conference on Web and Social Media
(ICWSM 2015
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