948 resultados para Hybrid agent models


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Comunicação apresentada na 17.ª conferência anual da NISPACee, realizada de 14 a 16 de Maio de 2009.

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Comunicação apresentada na 4th Annual ICPA - International Conference on Public Administration "Building bridges to the future: leadership and collaboration in public administration", na Universidade de Minnesota nos Estados Unidos, de 24 a 26 de setembro de 2008

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The paper proposes a numerical solution method for general equilibrium models with a continuum of heterogeneous agents, which combines elements of projection and of perturbation methods. The basic idea is to solve first for the stationary solutionof the model, without aggregate shocks but with fully specified idiosyncratic shocks. Afterwards one computes a first-order perturbation of the solution in the aggregate shocks. This approach allows to include a high-dimensional representation of the cross-sectional distribution in the state vector. The method is applied to a model of household saving with uninsurable income risk and liquidity constraints. The model includes not only productivity shocks, but also shocks to redistributive taxation, which cause substantial short-run variation in the cross-sectional distribution of wealth. If those shocks are operative, it is shown that a solution method based on very few statistics of the distribution is not suitable, while the proposed method can solve the model with high accuracy, at least for the case of small aggregate shocks. Techniques are discussed to reduce the dimension of the state space such that higher order perturbations are feasible.Matlab programs to solve the model can be downloaded.

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Wireless LANs are growing rapidly and security has always been a concern. We have implemented a hybrid system, which will not only detect active attacks like identity theft causing denial of service attacks, but will also detect the usage of access point discovery tools. The system responds in real time by sending out an alert to the network administrator.

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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Redes de Comunicação e Multimédia

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The interaction of a comet with the solar wind undergoes various stages as the comet’s activity varies along its orbit. For a comet like 67P/Churyumov–Gerasimenko, the target comet of ESA’s Rosetta mission, the various features include the formation of a Mach cone, the bow shock, and close to perihelion even a diamagnetic cavity. There are different approaches to simulate this complex interplay between the solar wind and the comet’s extended neutral gas coma which include magnetohydrodynamics (MHD) and hybrid-type models. The first treats the plasma as fluids (one fluid in basic single fluid MHD) and the latter treats the ions as individual particles under the influence of the local electric and magnetic fields. The electrons are treated as a charge-neutralizing fluid in both cases. Given the different approaches both models yield different results, in particular for a low production rate comet. In this paper we will show that these differences can be reduced when using a multifluid instead of a single-fluid MHD model and increase the resolution of the Hybrid model. We will show that some major features obtained with a hybrid type approach like the gyration of the cometary heavy ions and the formation of the Mach cone can be partially reproduced with the multifluid-type model.

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We extend in this paper some previous results concerning the differential-algebraic index of hybrid models of electrical and electronic circuits. Specifically, we present a comprehensive index characterization which holds without passivity requirements, in contrast to previous approaches, and which applies to nonlinear circuits composed of uncoupled, one-port devices. The index conditions, which are stated in terms of the forest structure of certain digraph minors, do not depend on the specific tree chosen in the formulation of the hybrid equations. Additionally, we show how to include memristors in hybrid circuit models; in this direction, we extend the index analysis to circuits including active memristors, which have been recently used in the design of nonlinear oscillators and chaotic circuits. We also discuss the extension of these results to circuits with controlled sources, making our framework of interest in the analysis of circuits with transistors, amplifiers, and other multiterminal devices.

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Here, I investigate the use of Bayesian updating rules applied to modeling how social agents change their minds in the case of continuous opinion models. Given another agent statement about the continuous value of a variable, we will see that interesting dynamics emerge when an agent assigns a likelihood to that value that is a mixture of a Gaussian and a uniform distribution. This represents the idea that the other agent might have no idea about what is being talked about. The effect of updating only the first moments of the distribution will be studied, and we will see that this generates results similar to those of the bounded confidence models. On also updating the second moment, several different opinions always survive in the long run, as agents become more stubborn with time. However, depending on the probability of error and initial uncertainty, those opinions might be clustered around a central value.

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Dissertation presented to obtain a Master degree in Biotechnology

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In many real world contexts individuals find themselves in situations where they have to decide between options of behaviour that serve a collective purpose or behaviours which satisfy one’s private interests, ignoring the collective. In some cases the underlying social dilemma (Dawes, 1980) is solved and we observe collective action (Olson, 1965). In others social mobilisation is unsuccessful. The central topic of social dilemma research is the identification and understanding of mechanisms which yield to the observed cooperation and therefore resolve the social dilemma. It is the purpose of this thesis to contribute this research field for the case of public good dilemmas. To do so, existing work that is relevant to this problem domain is reviewed and a set of mandatory requirements is derived which guide theory and method development of the thesis. In particular, the thesis focusses on dynamic processes of social mobilisation which can foster or inhibit collective action. The basic understanding is that success or failure of the required process of social mobilisation is determined by heterogeneous individual preferences of the members of a providing group, the social structure in which the acting individuals are contained, and the embedding of the individuals in economic, political, biophysical, or other external contexts. To account for these aspects and for the involved dynamics the methodical approach of the thesis is computer simulation, in particular agent-based modelling and simulation of social systems. Particularly conductive are agent models which ground the simulation of human behaviour in suitable psychological theories of action. The thesis develops the action theory HAPPenInGS (Heterogeneous Agents Providing Public Goods) and demonstrates its embedding into different agent-based simulations. The thesis substantiates the particular added value of the methodical approach: Starting out from a theory of individual behaviour, in simulations the emergence of collective patterns of behaviour becomes observable. In addition, the underlying collective dynamics may be scrutinised and assessed by scenario analysis. The results of such experiments reveal insights on processes of social mobilisation which go beyond classical empirical approaches and yield policy recommendations on promising intervention measures in particular.

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The main objective of this work was to investigate the impact of different hybridization concepts and levels of hybridization on fuel economy of a standard road vehicle where both conventional and non-conventional hybrid architectures are treated exactly in the same way from the point of view of overall energy flow optimization. Hybrid component models were developed and presented in detail as well as the simulations results mainly for NEDC cycle. The analysis was performed on four different parallel hybrid powertrain concepts: Hybrid Electric Vehicle (HEV), High Speed Flywheel Hybrid Vehicle (HSF-HV), Hydraulic Hybrid Vehicle (HHV) and Pneumatic Hybrid Vehicle (PHV). In order to perform equitable analysis of different hybrid systems, comparison was performed also on the basis of the same usable system energy storage capacity (i.e. 625kJ for HEV, HSF and the HHV) but in the case of pneumatic hybrid systems maximal storage capacity was limited by the size of the systems in order to comply with the packaging requirements of the vehicle. The simulations were performed within the IAV Gmbh - VeLoDyn software simulator based on Matlab / Simulink software package. Advanced cycle independent control strategy (ECMS) was implemented into the hybrid supervisory control unit in order to solve power management problem for all hybrid powertrain solutions. In order to maintain State of Charge within desired boundaries during different cycles and to facilitate easy implementation and recalibration of the control strategy for very different hybrid systems, Charge Sustaining Algorithm was added into the ECMS framework. Also, a Variable Shift Pattern VSP-ECMS algorithm was proposed as an extension of ECMS capabilities so as to include gear selection into the determination of minimal (energy) cost function of the hybrid system. Further, cycle-based energetic analysis was performed in all the simulated cases, and the results have been reported in the corresponding chapters.

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Integrated choice and latent variable (ICLV) models represent a promising new class of models which merge classic choice models with the structural equation approach (SEM) for latent variables. Despite their conceptual appeal, applications of ICLV models in marketing remain rare. We extend previous ICLV applications by first estimating a multinomial choice model and, second, by estimating hierarchical relations between latent variables. An empirical study on travel mode choice clearly demonstrates the value of ICLV models to enhance the understanding of choice processes. In addition to the usually studied directly observable variables such as travel time, we show how abstract motivations such as power and hedonism as well as attitudes such as a desire for flexibility impact on travel mode choice. Furthermore, we show that it is possible to estimate such a complex ICLV model with the widely available structural equation modeling package Mplus. This finding is likely to encourage more widespread application of this appealing model class in the marketing field.

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In this paper, we introduce B2DI model that extends BDI model to perform Bayesian inference under uncertainty. For scalability and flexibility purposes, Multiply Sectioned Bayesian Network (MSBN) technology has been selected and adapted to BDI agent reasoning. A belief update mechanism has been defined for agents, whose belief models are connected by public shared beliefs, and the certainty of these beliefs is updated based on MSBN. The classical BDI agent architecture has been extended in order to manage uncertainty using Bayesian reasoning. The resulting extended model, so-called B2DI, proposes a new control loop. The proposed B2DI model has been evaluated in a network fault diagnosis scenario. The evaluation has compared this model with two previously developed agent models. The evaluation has been carried out with a real testbed diagnosis scenario using JADEX. As a result, the proposed model exhibits significant improvements in the cost and time required to carry out a reliable diagnosis.