873 resultados para multi-agent systems
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The principles of adaptive routing and multi-agent control for information flows in IP-networks.
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The problems and methods for adaptive control and multi-agent processing of information in global telecommunication and computer networks (TCN) are discussed. Criteria for controllability and communication ability (routing ability) of dataflows are described. Multi-agent model for exchange of divided information resources in global TCN has been suggested. Peculiarities for adaptive and intelligent control of dataflows in uncertain conditions and network collisions are analyzed.
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The problem of multi-agent routing in static telecommunication networks with fixed configuration is considered. The problem is formulated in two ways: for centralized routing schema with the coordinator-agent (global routing) and for distributed routing schema with independent agents (local routing). For both schemas appropriate Hopfield neural networks (HNN) are constructed.
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It is proposed an agent approach for creation of intelligent intrusion detection system. The system allows detecting known type of attacks and anomalies in user activity and computer system behavior. The system includes different types of intelligent agents. The most important one is user agent based on neural network model of user behavior. Proposed approach is verified by experiments in real Intranet of Institute of Physics and Technologies of National Technical University of Ukraine "Kiev Polytechnic Institute”.
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A major challenge of modern teams lies in the coordination of the efforts not just of individuals within a team, but also of teams whose efforts are ultimately entwined with those of other teams. Despite this fact, much of the research on work teams fails to consider the external dependencies that exist in organizational teams and instead focuses on internal or within team processes. Multi-Team Systems Theory is used as a theoretical framework for understanding teams-of-teams organizational forms (Multi-Team Systems; MTS's); and leadership teams are proposed as one remedy that enable MTS members to dedicate needed resources to intra-team activities while ensuring effective synchronization of between-team activities. Two functions of leader teams were identified: strategy development and coordination facilitation; and a model was developed delineating the effects of the two leader roles on multi-team cognitions, processes, and performance.^ Three hundred eighty-four undergraduate psychology and business students participated in a laboratory simulation that modeled an MTS; each MTS was comprised of three, two-member teams each performing distinct but interdependent components of an F-22 battle simulation task. Two roles of leader teams supported in the literature were manipulated through training in a 2 (strategy training vs. control) x 2 (coordination training vs. control) design. Multivariate analysis of variance (MANOVA) and mediated regression analysis were used to test the study's hypotheses. ^ Results indicate that both training manipulations produced differences in the effectiveness of the intended form of leader behavior. The enhanced leader strategy training resulted in more accurate (but not more similar) MTS mental models, better inter-team coordination, and higher levels of multi-team (but not component team) performance. Moreover, mental model accuracy fully mediated the relationship between leader strategy and inter-team coordination; and inter-team coordination fully mediated the effect of leader strategy on multi-team performance. Leader coordination training led to better inter-team coordination, but not to higher levels of either team or multi-team performance. Mediated Input-Process-Output (I-P-O) relationships were not supported with leader coordination; rather, leader coordination facilitation and inter-team coordination uniquely contributed to component team and multi-team level performance. The implications of these findings and future research directions are also discussed. ^
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A methodology for formally modeling and analyzing software architecture of mobile agent systems provides a solid basis to develop high quality mobile agent systems, and the methodology is helpful to study other distributed and concurrent systems as well. However, it is a challenge to provide the methodology because of the agent mobility in mobile agent systems.^ The methodology was defined from two essential parts of software architecture: a formalism to define the architectural models and an analysis method to formally verify system properties. The formalism is two-layer Predicate/Transition (PrT) nets extended with dynamic channels, and the analysis method is a hierarchical approach to verify models on different levels. The two-layer modeling formalism smoothly transforms physical models of mobile agent systems into their architectural models. Dynamic channels facilitate the synchronous communication between nets, and they naturally capture the dynamic architecture configuration and agent mobility of mobile agent systems. Component properties are verified based on transformed individual components, system properties are checked in a simplified system model, and interaction properties are analyzed on models composing from involved nets. Based on the formalism and the analysis method, this researcher formally modeled and analyzed a software architecture of mobile agent systems, and designed an architectural model of a medical information processing system based on mobile agents. The model checking tool SPIN was used to verify system properties such as reachability, concurrency and safety of the medical information processing system. ^ From successful modeling and analyzing the software architecture of mobile agent systems, the conclusion is that PrT nets extended with channels are a powerful tool to model mobile agent systems, and the hierarchical analysis method provides a rigorous foundation for the modeling tool. The hierarchical analysis method not only reduces the complexity of the analysis, but also expands the application scope of model checking techniques. The results of formally modeling and analyzing the software architecture of the medical information processing system show that model checking is an effective and an efficient way to verify software architecture. Moreover, this system shows a high level of flexibility, efficiency and low cost of mobile agent technologies. ^
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Postprint
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Postprint
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Peer reviewed
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In a team of multiple agents, the pursuance of a common goal is a defining characteristic. Since agents may have different capabilities, and effects of actions may be uncertain, a common goal can generally only be achieved through a careful cooperation between the different agents. In this work, we propose a novel two-stage planner that combines online planning at both team level and individual level through a subgoal delegation scheme. The proposal brings the advantages of online planning approaches to the multi-agent setting. A number of modifications are made to a classical UCT approximate algorithm to (i) adapt it to the application domains considered, (ii) reduce the branching factor in the underlying search process, and (iii) effectively manage uncertain information of action effects by using information fusion mechanisms. The proposed online multi-agent planner reduces the cost of planning and decreases the temporal cost of reaching a goal, while significantly increasing the chance of success of achieving the common goal.
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A Fourier transform infrared gas-phase method is described herein and capable of deriving the vapour pressure of each pure component of a poorly volatile mixture and determining the relative vapour phase composition for each system. The performance of the present method has been validated using two standards (naphthalene and ferrocene), and a Raoult’s plot surface of a ternary system is reported as proof-of-principle. This technique is ideal for studying solutions comprising two, three, or more organic compounds dissolved in ionic liquids as they have no measurable vapour pressures.
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We apply Agent-Based Modeling and Simulation (ABMS) to investigate a set of problems in a retail context. Specifically, we are working to understand the relationship between human resource management practices and retail productivity. Despite the fact we are working within a relatively novel and complex domain, it is clear that intelligent agents do offer potential for developing organizational capabilities in the future. Our multi-disciplinary research team has worked with a UK department store to collect data and capture perceptions about operations from actors within departments. Based on this case study work, we have built a simulator that we present in this paper. We then use the simulator to gather empirical evidence regarding two specific management practices: empowerment and employee development.
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Reconfigurable hardware can be used to build a multitasking system where tasks are assigned to HW resources at run-time according to the requirements of the running applications. These tasks are frequently represented as direct acyclic graphs and their execution is typically controlled by an embedded processor that schedules the graph execution. In order to improve the efficiency of the system, the scheduler can apply prefetch and reuse techniques that can greatly reduce the reconfiguration latencies. For an embedded processor all these computations represent a heavy computational load that can significantly reduce the system performance. To overcome this problem we have implemented a HW scheduler using reconfigurable resources. In addition we have implemented both prefetch and replacement techniques that obtain as good results as previous complex SW approaches, while demanding just a few clock cycles to carry out the computations. We consider that the HW cost of the system (in our experiments 3% of a Virtex-II PRO xc2vp30 FPGA) is affordable taking into account the great efficiency of the techniques applied to hide the reconfiguration latency and the negligible run-time penalty introduced by the scheduler computations.
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Reconfigurable hardware can be used to build multi tasking systems that dynamically adapt themselves to the requirements of the running applications. This is especially useful in embedded systems, since the available resources are very limited and the reconfigurable hardware can be reused for different applications. In these systems computations are frequently represented as task graphs that are executed taking into account their internal dependencies and the task schedule. The management of the task graph execution is critical for the system performance. In this regard, we have developed two dif erent versions, a software module and a hardware architecture, of a generic task-graph execution manager for reconfigurable multi-tasking systems. The second version reduces the run-time management overheads by almost two orders of magnitude. Hence it is especially suitable for systems with exigent timing constraints. Both versions include specific support to optimize the reconfiguration process.
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The aim of this thesis is to present exact and heuristic algorithms for the integrated planning of multi-energy systems. The idea is to disaggregate the energy system, starting first with its core the Central Energy System, and then to proceed towards the Decentral part. Therefore, a mathematical model for the generation expansion operations to optimize the performance of a Central Energy System system is first proposed. To ensure that the proposed generation operations are compatible with the network, some extensions of the existing network are considered as well. All these decisions are evaluated both from an economic viewpoint and from an environmental perspective, as specific constraints related to greenhouse gases emissions are imposed in the formulation. Then, the thesis presents an optimization model for solar organic Rankine cycle in the context of transactive energy trading. In this study, the impact that this technology can have on the peer-to-peer trading application in renewable based community microgrids is inspected. Here the consumer becomes a prosumer and engages actively in virtual trading with other prosumers at the distribution system level. Moreover, there is an investigation of how different technological parameters of the solar Organic Rankine Cycle may affect the final solution. Finally, the thesis introduces a tactical optimization model for the maintenance operations’ scheduling phase of a Combined Heat and Power plant. Specifically, two types of cleaning operations are considered, i.e., online cleaning and offline cleaning. Furthermore, a piecewise linear representation of the electric efficiency variation curve is included. Given the challenge of solving the tactical management model, a heuristic algorithm is proposed. The heuristic works by solving the daily operational production scheduling problem, based on the final consumer’s demand and on the electricity prices. The aggregate information from the operational problem is used to derive maintenance decisions at a tactical level.