358 research outputs found

    Sensor networks security based on sensitive robots agents. A conceptual model

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    Multi-agent systems are currently applied to solve complex problems. The security of networks is an eloquent example of a complex and difficult problem. A new model-concept Hybrid Sensitive Robot Metaheuristic for Intrusion Detection is introduced in the current paper. The proposed technique could be used with machine learning based intrusion detection techniques. The new model uses the reaction of virtual sensitive robots to different stigmergic variables in order to keep the tracks of the intruders when securing a sensor network.Comment: 5 page

    Autonomous three-dimensional formation flight for a swarm of unmanned aerial vehicles

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    This paper investigates the development of a new guidance algorithm for a formation of unmanned aerial vehicles. Using the new approach of bifurcating potential fields, it is shown that a formation of unmanned aerial vehicles can be successfully controlled such that verifiable autonomous patterns are achieved, with a simple parameter switch allowing for transitions between patterns. The key contribution that this paper presents is in the development of a new bounded bifurcating potential field that avoids saturating the vehicle actuators, which is essential for real or safety-critical applications. To demonstrate this, a guidance and control method is developed, based on a six-degreeof-freedom linearized aircraft model, showing that, in simulation, three-dimensional formation flight for a swarm of unmanned aerial vehicles can be achieved

    An Agent-Based Approach to Self-Organized Production

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    The chapter describes the modeling of a material handling system with the production of individual units in a scheduled order. The units represent the agents in the model and are transported in the system which is abstracted as a directed graph. Since the hindrances of units on their path to the destination can lead to inefficiencies in the production, the blockages of units are to be reduced. Therefore, the units operate in the system by means of local interactions in the conveying elements and indirect interactions based on a measure of possible hindrances. If most of the units behave cooperatively ("socially"), the blockings in the system are reduced. A simulation based on the model shows the collective behavior of the units in the system. The transport processes in the simulation can be compared with the processes in a real plant, which gives conclusions about the consequencies for the production based on the superordinate planning.Comment: For related work see http://www.soms.ethz.c

    Fostering collective intelligence education

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    New educational models are necessary to update learning environments to the digitally shared communication and information. Collective intelligence is an emerging field that already has a significant impact in many areas and will have great implications in education, not only from the side of new methodologies but also as a challenge for education. This paper proposes an approach to a collective intelligence model of teaching using Internet to combine two strategies: idea management and real time assessment in the class. A digital tool named Fabricius has been created supporting these two elements to foster the collaboration and engagement of students in the learning process. As a result of the research we propose a list of KPI trying to measure individual and collective performance. We are conscious that this is just a first approach to define which aspects of a class following a course can be qualified and quantified.Postprint (published version

    Self-organization of vortices in type-II superconductors during magnetic relaxation

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    We revise the applicability of the theory of self-organized criticality (SOC) to the process of magnetic relaxation in type-II superconductors. The driving parameter of self-organization of vortices is the energy barrier for flux creep and not the current density. The power spectrum of the magnetic noise due to vortex avalanches is calculated and is predicted to vary with time during relaxation.Comment: RevTex, 5 pages, 2 PS figures. Accepted in Phys. Rev.

    Effects of group composition and level of selection in the evolution of cooperation in artificial ants

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    Since ants and other social insects have long generation time, it is very difficult for biologists to study the origin of complex social organization by guided evolution (a process where the evolution of a trait can be followed during experimental evolution). Here we use colonies of artificial ants implemented as small mobile robots with simple vision and communication abilities to explore these issues. In this paper, we present results concerning the role of relatedness (genetic similarity) and levels of selection (individual and colony-level selection) on the evolution of cooperation and division of labor in simulated ant colonies. In order to ensure thorough statistical analysis, the evolutionary experiments, herein reported, have been carried out using "minimalist" simulations of the collective robotics evolutionary setup. The results show that altruistic behaviors have low probability of emerging in heterogeneous colonies evolving under individual-level selection and that colonies with high genetic relatedness display better performance

    Experiments in vortex avalanches

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    Avalanche dynamics is found in many phenomena spanning from earthquakes to the evolution of species. It can be also found in vortex matter when a type II superconductor is externally driven, for example, by increasing the magnetic field. Vortex avalanches associated with thermal instabilities can be an undesirable effect for applications, but "dynamically driven" avalanches emerging from the competition between intervortex interactions and quenched disorder constitute an interesting scenario to test theoretical ideas related with non-equilibrium dynamics. However, differently from the equilibrium phases of vortex matter in type II superconductors, the study of the corresponding dynamical phases - in which avalanches can play a role - is still in its infancy. In this paper we critically review relevant experiments performed in the last decade or so, emphasizing the ability of different experimental techniques to establish the nature and statistical properties of the observed avalanche behavior.Comment: To be published in Reviews of Modern Physics April 2004. 17 page

    Phase Transition in the Takayasu Model with Desorption

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    We study a lattice model where particles carrying different masses diffuse, coalesce upon contact, and also unit masses adsorb to a site with rate qq or desorb from a site with nonzero mass with rate pp. In the limit p=0p=0 (without desorption), our model reduces to the well studied Takayasu model where the steady-state single site mass distribution has a power law tail P(m)∌m−τP(m)\sim m^{-\tau} for large mass. We show that varying the desorption rate pp induces a nonequilibrium phase transition in all dimensions. For fixed qq, there is a critical pc(q)p_c(q) such that if p<pc(q)p<p_c(q), the steady state mass distribution, P(m)∌m−τP(m)\sim m^{-\tau} for large mm as in the Takayasu case. For p=pc(q)p=p_c(q), we find P(m)∌m−τcP(m)\sim m^{-\tau_c} where τc\tau_c is a new exponent, while for p>pc(q)p>p_c(q), P(m)∌exp⁥(−m/m∗)P(m)\sim \exp(-m/m^*) for large mm. The model is studied analytically within a mean field theory and numerically in one dimension.Comment: RevTex, 11 pages including 5 figures, submitted to Phys. Rev.

    Individualization as driving force of clustering phenomena in humans

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    One of the most intriguing dynamics in biological systems is the emergence of clustering, the self-organization into separated agglomerations of individuals. Several theories have been developed to explain clustering in, for instance, multi-cellular organisms, ant colonies, bee hives, flocks of birds, schools of fish, and animal herds. A persistent puzzle, however, is clustering of opinions in human populations. The puzzle is particularly pressing if opinions vary continuously, such as the degree to which citizens are in favor of or against a vaccination program. Existing opinion formation models suggest that "monoculture" is unavoidable in the long run, unless subsets of the population are perfectly separated from each other. Yet, social diversity is a robust empirical phenomenon, although perfect separation is hardly possible in an increasingly connected world. Considering randomness did not overcome the theoretical shortcomings so far. Small perturbations of individual opinions trigger social influence cascades that inevitably lead to monoculture, while larger noise disrupts opinion clusters and results in rampant individualism without any social structure. Our solution of the puzzle builds on recent empirical research, combining the integrative tendencies of social influence with the disintegrative effects of individualization. A key element of the new computational model is an adaptive kind of noise. We conduct simulation experiments to demonstrate that with this kind of noise, a third phase besides individualism and monoculture becomes possible, characterized by the formation of metastable clusters with diversity between and consensus within clusters. When clusters are small, individualization tendencies are too weak to prohibit a fusion of clusters. When clusters grow too large, however, individualization increases in strength, which promotes their splitting.Comment: 12 pages, 4 figure
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