767 resultados para cooperative coevolutionary algorithm
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ln this work, it was deveIoped a parallel cooperative genetic algorithm with different evolution behaviors to train and to define architectures for MuItiIayer Perceptron neural networks. MuItiIayer Perceptron neural networks are very powerful tools and had their use extended vastIy due to their abiIity of providing great resuIts to a broad range of appIications. The combination of genetic algorithms and parallel processing can be very powerful when applied to the Iearning process of the neural network, as well as to the definition of its architecture since this procedure can be very slow, usually requiring a lot of computational time. AIso, research work combining and appIying evolutionary computation into the design of neural networks is very useful since most of the Iearning algorithms deveIoped to train neural networks only adjust their synaptic weights, not considering the design of the networks architecture. Furthermore, the use of cooperation in the genetic algorithm allows the interaction of different populations, avoiding local minima and helping in the search of a promising solution, acceIerating the evolutionary process. Finally, individuaIs and evolution behavior can be exclusive on each copy of the genetic algorithm running in each task enhancing the diversity of populations
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The cooperative motion algorithm was applied on the molecular simulation of complex chemical reactions and macromolecular orientation phenomena in confined geometries. First, we investigated the case of equilibrium step-growth polymerization in lamellae, pores and droplets. In such systems, confinement was quantified as the area/volume ratio. Results showed that, as confinement increases, polymerization becomes slower and the average molecular weight (MW) at equilibrium decreases. This is caused by the sterical hindrance imposed by the walls since chain growth reactions in their close vicinity have less realization possibilities. For reactions inside droplets at surfaces, contact angles usually increased after polymerization to compensate conformation restrictions imposed by confinement upon growing chains. In a second investigation, we considered monodisperse and chemically inert chains and focused on the effect of confinement on chain orientation. Simulations of thin polymer films showed that chains are preferably oriented parallel to the surface. Orientation increases as MW increases or as film thickness d decreases, in qualitative agreement with experiments with low MW polystyrene. It is demonstrated that the orientation of simulated chains results from a size effect, being a function of the ratio between chain end-to-end distance and d. This study was complemented by experiments with thin films of pi-conjugated polymers like MEH-PPV. Anisotropic refractive index measurements were used to analyze chain orientation. With increasing MW, orientation is enhanced. However, for MEH-PPV, orientation does not depend on d even at thicknesses much larger than the chain contour length. This contradiction with simulations was discussed by considering additional causes for orientation, for instance the appearance of nematic-like ordering in polymer films. In another investigation, we simulated droplet evaporation at soluble surfaces and reproduced the formation of wells surrounded by ringlike deposits at the surface, as observed experimentally. In our simulations, swollen substrate particles migrate to the border of the droplet to minimize the contact between solvent and vacuum, which costs the most energy. Deposit formation in the beginning of evaporation results in pinning of the droplet. When polymer chains at the substrate surface have strong uniaxial orientation, the resulting pattern is no longer similar to a ring but to a pair of half-moons. In a final stage, as an extension for the model developed for polymerization in nanoreactors, we studied the effect of geometrical confinement on a hypothetical oscillating reaction following the mechanism of the so called periodically forced Brusselator. It was shown that a reaction which is chaotic in the bulk may be driven to periodicity by confinement and vice-versa, opening new perspectives for chaos control.
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The role of T-cells within the immune system is to confirm and assess anomalous situations and then either respond to or tolerate the source of the effect. To illustrate how these mechanisms can be harnessed to solve real-world problems, we present the blueprint of a T-cell inspired algorithm for computer security worm detection. We show how the three central T-cell processes, namely T-cell maturation, differentiation and proliferation, naturally map into this domain and further illustrate how such an algorithm fits into a complete immune inspired computer security system and framework.
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The role of T-cells within the immune system is to confirm and assess anomalous situations and then either respond to or tolerate the source of the effect. To illustrate how these mechanisms can be harnessed to solve real-world problems, we present the blueprint of a T-cell inspired algorithm for computer security worm detection. We show how the three central T-cell processes, namely T-cell maturation, differentiation and proliferation, naturally map into this domain and further illustrate how such an algorithm fits into a complete immune inspired computer security system and framework.
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Due to the growing complexity and adaptability requirements of real-time embedded systems, which often exhibit unrestricted inter-dependencies among supported services and user-imposed quality constraints, it is increasingly difficult to optimise the level of service of a dynamic task set within an useful and bounded time. This is even more difficult when intending to benefit from the full potential of an open distributed cooperating environment, where service characteristics are not known beforehand. This paper proposes an iterative refinement approach for a service’s QoS configuration taking into account services’ inter-dependencies and quality constraints, and trading off the achieved solution’s quality for the cost of computation. Extensive simulations demonstrate that the proposed anytime algorithm is able to quickly find a good initial solution and effectively optimises the rate at which the quality of the current solution improves as the algorithm is given more time to run. The added benefits of the proposed approach clearly surpass its reducedoverhead.
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La coordinació i assignació de tasques en entorns distribuïts ha estat un punt important de la recerca en els últims anys i aquests temes són el cor dels sistemes multi-agent. Els agents en aquests sistemes necessiten cooperar i considerar els altres agents en les seves accions i decisions. A més a més, els agents han de coordinar-se ells mateixos per complir tasques complexes que necessiten més d'un agent per ser complerta. Aquestes tasques poden ser tan complexes que els agents poden no saber la ubicació de les tasques o el temps que resta abans de que les tasques quedin obsoletes. Els agents poden necessitar utilitzar la comunicació amb l'objectiu de conèixer la tasca en l'entorn, en cas contrari, poden perdre molt de temps per trobar la tasca dins de l'escenari. De forma similar, el procés de presa de decisions distribuït pot ser encara més complexa si l'entorn és dinàmic, amb incertesa i en temps real. En aquesta dissertació, considerem entorns amb sistemes multi-agent amb restriccions i cooperatius (dinàmics, amb incertesa i en temps real). En aquest sentit es proposen dues aproximacions que permeten la coordinació dels agents. La primera és un mecanisme semi-centralitzat basat en tècniques de subhastes combinatòries i la idea principal es minimitzar el cost de les tasques assignades des de l'agent central cap als equips d'agents. Aquest algoritme té en compte les preferències dels agents sobre les tasques. Aquestes preferències estan incloses en el bid enviat per l'agent. La segona és un aproximació d'scheduling totalment descentralitzat. Això permet als agents assignar les seves tasques tenint en compte les preferències temporals sobre les tasques dels agents. En aquest cas, el rendiment del sistema no només depèn de la maximització o del criteri d'optimització, sinó que també depèn de la capacitat dels agents per adaptar les seves assignacions eficientment. Addicionalment, en un entorn dinàmic, els errors d'execució poden succeir a qualsevol pla degut a la incertesa i error de accions individuals. A més, una part indispensable d'un sistema de planificació és la capacitat de re-planificar. Aquesta dissertació també proveeix una aproximació amb re-planificació amb l'objectiu de permetre als agent re-coordinar els seus plans quan els problemes en l'entorn no permeti la execució del pla. Totes aquestes aproximacions s'han portat a terme per permetre als agents assignar i coordinar de forma eficient totes les tasques complexes en un entorn multi-agent cooperatiu, dinàmic i amb incertesa. Totes aquestes aproximacions han demostrat la seva eficiència en experiments duts a terme en l'entorn de simulació RoboCup Rescue.
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This study investigates the superposition-based cooperative transmission system. In this system, a key point is for the relay node to detect data transmitted from the source node. This issued was less considered in the existing literature as the channel is usually assumed to be flat fading and a priori known. In practice, however, the channel is not only a priori unknown but subject to frequency selective fading. Channel estimation is thus necessary. Of particular interest is the channel estimation at the relay node which imposes extra requirement for the system resources. The authors propose a novel turbo least-square channel estimator by exploring the superposition structure of the transmission data. The proposed channel estimator not only requires no pilot symbols but also has significantly better performance than the classic approach. The soft-in-soft-out minimum mean square error (MMSE) equaliser is also re-derived to match the superimposed data structure. Finally computer simulation results are shown to verify the proposed algorithm.
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This paper proposes the full interference cancellation (FIC) algorithm to cancel the inter-relay interference (IRI) in the two-path cooperative system. Arising from simultaneous data transmission from the source and relay nodes, IRI may significantly decrease the performance if it is not carefully handled. Compared to the existing partial interference cancellation (PIC) scheme, the FIC approach is more robust yet with less complexity. Numerical results are also given to verify the proposed scheme.
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In this paper, dual-hop amplify-and-forward (AF) cooperative systems in the presence of in-phase and quadrature-phase (I/Q) imbalance, which refers to the mismatch between components in I and Q branches, are investigated. First, we analyze the performance of the considered AF cooperative protocol without compensation for I/Q imbalance as the benchmark. Furthermore, a compensation algorithm for I/Q imbalance is proposed, which makes use of the received signals at the destination, from the source and relay nodes, together with their conjugations to detect the transmitted signal. The performance of the AF cooperative system under study is evaluated in terms of average symbol error probability (SEP), which is derived considering transmission over Rayleigh fading channels. Numerical results are provided and show that the proposed compensation algorithm can efficiently mitigate the effect of I/Q imbalance.
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In this study, dual-hop channel state information-assisted amplify-and-forward (AF) cooperative systems in the presence of in-phase and quadrature-phase (I/Q) imbalance, which refers to the mismatch between components in the I and Q branches, are investigated. First, the authors analyse the performance of the considered AF cooperative protocol without compensation for the I/Q imbalance as the benchmark. Then, a compensation algorithm for the I/Q imbalance is proposed, which makes use of the received signals at the destination, from the source and the relay nodes, together with their conjugations to detect the transmitted signal. Moreover, the authors study the considered AF cooperative system implemented with the opportunistic relay selection and the proposed compensation mechanism for the I/Q imbalance. The performance of the AF cooperative system under study is evaluated in terms of average symbol error probability, which is derived by considering transmission in a Rayleigh fading environment. Numerical results are provided and show that the proposed compensation algorithm can efficiently mitigate the effect of the I/Q imbalance. On the other hand, it is observed that the AF cooperative system with opportunistic relay selection acquires a performance gain beyond that without relay selection.
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This thesis adresses the problem of localization, and analyzes its crucial aspects, within the context of cooperative WSNs. The three main issues discussed in the following are: network synchronization, position estimate and tracking. Time synchronization is a fundamental requirement for every network. In this context, a new approach based on the estimation theory is proposed to evaluate the ultimate performance limit in network time synchronization. In particular the lower bound on the variance of the average synchronization error in a fully connected network is derived by taking into account the statistical characterization of the Message Delivering Time (MDT) . Sensor network localization algorithms estimate the locations of sensors with initially unknown location information by using knowledge of the absolute positions of a few sensors and inter-sensor measurements such as distance and bearing measurements. Concerning this issue, i.e. the position estimate problem, two main contributions are given. The first is a new Semidefinite Programming (SDP) framework to analyze and solve the problem of flip-ambiguity that afflicts range-based network localization algorithms with incomplete ranging information. The occurrence of flip-ambiguous nodes and errors due to flip ambiguity is studied, then with this information a new SDP formulation of the localization problem is built. Finally a flip-ambiguity-robust network localization algorithm is derived and its performance is studied by Monte-Carlo simulations. The second contribution in the field of position estimate is about multihop networks. A multihop network is a network with a low degree of connectivity, in which couples of given any nodes, in order to communicate, they have to rely on one or more intermediate nodes (hops). Two new distance-based source localization algorithms, highly robust to distance overestimates, typically present in multihop networks, are presented and studied. The last point of this thesis discuss a new low-complexity tracking algorithm, inspired by the Fano’s sequential decoding algorithm for the position tracking of a user in a WLAN-based indoor localization system.
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This thesis deals with distributed control strategies for cooperative control of multi-robot systems. Specifically, distributed coordination strategies are presented for groups of mobile robots. The formation control problem is initially solved exploiting artificial potential fields. The purpose of the presented formation control algorithm is to drive a group of mobile robots to create a completely arbitrarily shaped formation. Robots are initially controlled to create a regular polygon formation. A bijective coordinate transformation is then exploited to extend the scope of this strategy, to obtain arbitrarily shaped formations. For this purpose, artificial potential fields are specifically designed, and robots are driven to follow their negative gradient. Artificial potential fields are then subsequently exploited to solve the coordinated path tracking problem, thus making the robots autonomously spread along predefined paths, and move along them in a coordinated way. Formation control problem is then solved exploiting a consensus based approach. Specifically, weighted graphs are used both to define the desired formation, and to implement collision avoidance. As expected for consensus based algorithms, this control strategy is experimentally shown to be robust to the presence of communication delays. The global connectivity maintenance issue is then considered. Specifically, an estimation procedure is introduced to allow each agent to compute its own estimate of the algebraic connectivity of the communication graph, in a distributed manner. This estimate is then exploited to develop a gradient based control strategy that ensures that the communication graph remains connected, as the system evolves. The proposed control strategy is developed initially for single-integrator kinematic agents, and is then extended to Lagrangian dynamical systems.
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This Ph.D. dissertation reports on the work performed at the Wireless Communication Laboratory - University of Bologna and National Research Council - as well as, for six months, at the Fraunhofer Institute for Integrated Circuit (IIS) in Nürnberg. The work of this thesis is in the area of wireless communications, especially with regards to cooperative communications aspects in narrow-band and ultra-wideband systems, cooperative links characterization, network geometry, power allocation techniques,and synchronization between nodes. The underpinning of this work is devoted to developing a general framework for design and analysis of wireless cooperative communication systems, which depends on propagation environment, transmission technique, diversity method, power allocation for various scenarios and relay positions. The optimal power allocation for minimizing the bit error probability at the destination is derived. In addition, a syncronization algorithm for master-slave communications is proposed with the aim of jointly compensate the clock drift and offset of wireless nodes composing the network.
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Recently, Branzei, Dimitrov, and Tijs (2003) introduced cooperative interval-valued games. Among other insights, the notion of an interval core has been coined and proposed as a solution concept for interval-valued games. In this paper we will present a general mathematical programming algorithm which can be applied to find an element in the interval core. As an example, we discuss lot sizing with uncertain demand to provide an application for interval-valued games and to demonstrate how interval core elements can be computed. Also, we reveal that pitfalls exist if interval core elements are computed in a straightforward manner by considering the interval borders separately.
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Nonparametric belief propagation (NBP) is a well-known particle-based method for distributed inference in wireless networks. NBP has a large number of applications, including cooperative localization. However, in loopy networks NBP suffers from similar problems as standard BP, such as over-confident beliefs and possible nonconvergence. Tree-reweighted NBP (TRW-NBP) can mitigate these problems, but does not easily lead to a distributed implementation due to the non-local nature of the required so-called edge appearance probabilities. In this paper, we propose a variation of TRWNBP, suitable for cooperative localization in wireless networks. Our algorithm uses a fixed edge appearance probability for every edge, and can outperform standard NBP in dense wireless networks.