771 resultados para Agent-Based Models
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In this paper, we describe agent-based content retrieval for opportunistic networks, where requesters can delegate content retrieval to agents, which retrieve the content on their behalf. The approach has been implemented in CCNx, the open source CCN framework, and evaluated on Android smart phones. Evaluations have shown that the overhead of agent delegation is only noticeable for very small content. For content larger than 4MB, agent-based content retrieval can even result in a throughput increase of 20% compared to standard CCN download applications. The requester asks every probe interval for agents that have retrieved the desired content. Evaluations have shown that a probe interval of 30s delivers the best overall performance in our scenario because the number of transmitted notification messages can be decreased by up to 80% without significantly increasing the download time.
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The Agent-Based Modelling and simulation (ABM) is a rather new approach for studying complex systems withinteracting autonomous agents that has lately undergone great growth in various fields such as biology, physics, social science, economics and business. Efforts to model and simulate the highly complex cement hydration process have been made over the past 40 years, with the aim of predicting the performance of concrete and designing innovative and enhanced cementitious materials. The ABM presented here - based on previous work - focuses on the early stages of cement hydration by modelling the physical-chemical processes at the particle level. The model considers the cement hydration process as a time and 3D space system, involving multiple diffusing and reacting species of spherical particles. Chemical reactions are simulated by adaptively selecting discrete stochastic simulation for the appropriate reaction, whenever that is necessary. Interactions between particles are also considered. The model has been inspired by reported cellular automata?s approach which provides detailed predictions of cement microstructure at the expense of significant computational difficulty. The ABM approach herein seeks to bring about an optimal balance between accuracy and computational efficiency.
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The agent-based model presented here, comprises an algorithm that computes the degree of hydration, the water consumption and the layer thickness of C-S-H gel as functions of time for different temperatures and different w/c ratios. The results are in agreement with reported experimental studies, demonstrating the applicability of the model. As the available experimental results regarding elevated curing temperature are scarce, the model could be recalibrated in the future. Combining the agent-based computational model with TGA analysis, a semiempirical method is achieved to be used for better understanding the microstructure development in ordinary cement pastes and to predict the influence of temperature on the hydration process.
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This paper describes an agent-based approach for the simulation of air traffic management (ATM) in Europe that was designed to help analyze proposals for future ATM systems. This approach is able to represent new collaborative deci-sion processes for flow traffic management, it uses an intermediate level of ab-straction (useful for simulations at larger scales), and was designed to be a practi-cal tool (open and reusable) for the development of different ATM studies. It was successfully applied in three studies related to the design of future ATM systems in Europe.
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The aim of this chapter is to discuss the applicability of recently proposed knowledge modelling tools to the development of agent-based systems. The discussion is derived from the real world experience of a particular software tool called KSM (Knowledge Structure Manager). The chapter provides details about this tool and then proceeds to show in which forms the software may be used to support the development of agent-based systems. Two multiagent systems, one in the field of telecommunications management and the other one in the field of flood control, are described. Conclusions about these studies are presented, summarizing the main contributions that knowledge modelling tools can bring to the development of agent-based systems.
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This paper argues about the utility of advanced knowledge-based techniques to develop web-based applications that help consumers in finding products within marketplaces in e-commerce. In particular, we describe the idea of model-based approach to develop a shopping agent that dynamically configures a product according to the needs and preferences of customers. Finally, the paper summarizes the advantages provided by this approach.
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This paper describes a general approach for real time traffic management support using knowledge based models. Recognizing that human intervention is usually required to apply the current automatic traffic control systems, it is argued that there is a need for an additional intelligent layer to help operators to understand traffic problems and to make the best choice of strategic control actions that modify the assumption framework of the existing systems.
Resumo:
The primary hypothesis stated by this paper is that the use of social choice theory in Ambient Intelligence systems can improve significantly users satisfaction when accessing shared resources. A research methodology based on agent based social simulations is employed to support this hypothesis and to evaluate these benefits. The result is a six-fold contribution summarized as follows. Firstly, several considerable differences between this application case and the most prominent social choice application, political elections, have been found and described. Secondly, given these differences, a number of metrics to evaluate different voting systems in this scope have been proposed and formalized. Thirdly, given the presented application and the metrics proposed, the performance of a number of well known electoral systems is compared. Fourthly, as a result of the performance study, a novel voting algorithm capable of obtaining the best balance between the metrics reviewed is introduced. Fifthly, to improve the social welfare in the experiments, the voting methods are combined with cluster analysis techniques. Finally, the article is complemented by a free and open-source tool, VoteSim, which ensures not only the reproducibility of the experimental results presented, but also allows the interested reader to adapt the case study presented to different environments.
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Trabalho apresentado na Conferência CPE-POWERENG 2016, 29 junho a 01 de julho 2016, Bydgoszcz, Polónia
Resumo:
L'obiettivo della tesi è dimostrare l'utilità e i vantaggi che può fornire il Self-Management del diabete mellito di tipo 1 in un sistema di mobile Health a partire da un modello computazionale Agent-Based. Viene quindi affrontata in maniera approfondita la tematica del mobile Health ed il suo sviluppo nei paesi a basso/medio reddito, illustrando i risultati ottenuti dalla ricerca scientifica fino ad oggi, ed il concetto di Self-Management di malattie croniche, un processo di cura caratterizzato dalla partecipazione autonoma del paziente stesso, fornendo una panoramica degli approcci computazionali sviluppati. Viene quindi studiato il diabete mellito in ogni sua caratteristica, seguito dall'illustrazione di diverse applicazioni per la gestione autonoma della suddetta patologia tutt'ora in commercio. Nel caso di studio vengono effettuate diverse simulazioni, tramite la piattaforma di simulazione MASON, per realizzare varie dinamiche della rete fisiologica di un paziente al fine di stabilire feedback qualitativi per il Self-Management della patologia.