871 resultados para Agent based moduling stimulation
Resumo:
Este trabalho aborda o estudo do comportamento mecânico e térmico do nanocompósito híbrido de polipropileno com uma argila brasileira bentonítica do Estado da Paraíba (PB), conhecida como \"chocolate\" com concentração de 1, 2 e 5 % em massa com a adição de 1 e 2 % em massa de celulose proveniente de papel descartado. Foi utilizado nesse nanocompósito o agente compatibilizante polipropileno graftizado com anidrido maleico PP-g-AM com 3 % de concentração em massa, através da técnica de intercalação do fundido utilizando uma extrusora de dupla-rosca e, em seguida, os corpos de prova foram confeccionados em uma injetora. O comportamento mecânico foi avaliado pelos ensaios de tração, flexão e impacto. O comportamento térmico foi avaliado pelas técnicas de calorimetria exploratória diferencial (DSC) e termogravimetria (TGA). A morfologia dos nanocompósitos foi estudada pela técnica de microscopia eletrônica de varredura (MEV). A argila, a celulose e os nanocompósitos híbridos foram caracterizados por difração de raios X (DRX), fluorescência de raios X (FRX) e espectroscopia no infravermelho (FTIR). Nos ensaios mecânicos de tração houve um aumento de 11 % na tensão máxima em tração e 15 % no módulo de Young, para o nanocompósito com argila, PPA 5 %. No ensaio de impacto Izod, o nanocompósito com argila, PPA 2 % obteve um aumento de 63 % na resistência ao impacto. Para o nanocompósito híbrido PPAC 1 % houve aumento de 8 % na tensão máxima em tração e para o nanocompósito híbrido PPAC 2 % houve aumento de 14 % na resistência ao impacto.
Resumo:
Um dos aspectos regulatórios fundamentais para o mercado imobiliário no Brasil são os limites para obtenção de financiamento no Sistema Financeiro de Habitação. Esses limites podem ser definidos de forma a aumentar ou reduzir a oferta de crédito neste mercado, alterando o comportamento dos seus agentes e, com isso, o preço de mercado dos imóveis. Neste trabalho, propomos um modelo de formação de preços no mercado imobiliário brasileiro com base no comportamento dos agentes que o compõem. Os agentes vendedores têm comportamento heterogêneo e são influenciados pela demanda histórica, enquanto que os agentes compradores têm o seu comportamento determinado pela disponibilidade de crédito. Esta disponibilidade de crédito, por sua vez, é definida pelos limites para concessão de financiamento no Sistema Financeiro de Habitação. Verificamos que o processo markoviano que descreve preço de mercado converge para um sistema dinâmico determinístico quando o número de agentes aumenta, e analisamos o comportamento deste sistema dinâmico. Mostramos qual é a família de variáveis aleatórias que representa o comportamento dos agentes vendedores de forma que o sistema apresente um preço de equilíbrio não trivial, condizente com a realidade. Verificamos ainda que o preço de equilíbrio depende não só das regras de concessão de financiamento no Sistema Financeiro de Habitação, como também do preço de reserva dos compradores e da memória e da sensibilidade dos vendedores a alterações na demanda. A memória e a sensibilidade dos vendedores podem levar a oscilações de preços acima ou abaixo do preço de equilíbrio (típicas de processos de formação de bolhas); ou até mesmo a uma bifurcação de Neimark-Sacker, quando o sistema apresenta dinâmica oscilatória estável.
Resumo:
This paper investigates the impacts of high interest rates for borrowed capital and credit restrictions on the structural development of four European regions. The method used is the model AgriPoliS which is a spatial-dynamic agent-based model. It is able to provide aggregated results at the regional level, but very individual results as well by considering farms as independent entities. Farms can choose between different investment options during the simulation. Several scenarios with different interest rates for borrowed capital on the one hand as well as with different levels of credit restrictions on the other hand are tested and compared. Results show that higher interest rates have less impact on declining production branches than on expanding ones. If they have the possibility farms invest in the most profitable production branch which relative profitability might have changed with high interest rates. Credit restrictions lead farms to choose smaller and cheaper investments than expensive and large ones. Results also show that income losses in both cases due to under-investment compared to the reference situation are partially compensated by lower rental prices. The impacts on structural change also differ depending on the region and the initial situation. In summary, credit subsidies or imperfections on credit markets might have indirect impacts on the type of dominant investment and therefore on the whole regional agricultural sector as well.
Resumo:
The design, development, and use of complex systems models raises a unique class of challenges and potential pitfalls, many of which are commonly recurring problems. Over time, researchers gain experience in this form of modeling, choosing algorithms, techniques, and frameworks that improve the quality, confidence level, and speed of development of their models. This increasing collective experience of complex systems modellers is a resource that should be captured. Fields such as software engineering and architecture have benefited from the development of generic solutions to recurring problems, called patterns. Using pattern development techniques from these fields, insights from communities such as learning and information processing, data mining, bioinformatics, and agent-based modeling can be identified and captured. Collections of such 'pattern languages' would allow knowledge gained through experience to be readily accessible to less-experienced practitioners and to other domains. This paper proposes a methodology for capturing the wisdom of computational modelers by introducing example visualization patterns, and a pattern classification system for analyzing the relationship between micro and macro behaviour in complex systems models. We anticipate that a new field of complex systems patterns will provide an invaluable resource for both practicing and future generations of modelers.
Resumo:
Knowledge maintenance is a major challenge for both knowledge management and the Semantic Web. Operating over the Semantic Web, there will be a network of collaborating agents, each with their own ontologies or knowledge bases. Change in the knowledge state of one agent may need to be propagated across a number of agents and their associated ontologies. The challenge is to decide how to propagate a change of knowledge state. The effects of a change in knowledge state cannot be known in advance, and so an agent cannot know who should be informed unless it adopts a simple ‘tell everyone – everything’ strategy. This situation is highly reminiscent of the classic Frame Problem in AI. We argue that for agent-based technologies to succeed, far greater attention must be given to creating an appropriate model for knowledge update. In a closed system, simple strategies are possible (e.g. ‘sleeping dog’ or ‘cheap test’ or even complete checking). However, in an open system where cause and effect are unpredictable, a coherent cost-benefit based model of agent interaction is essential. Otherwise, the effectiveness of every act of knowledge update/maintenance is brought into question.
Resumo:
Challenges of returnable transport equipment (RTE) management continue to heighten as the popularity of their usage magnifies. Logistics companies are investigating the implementation of radio-frequency identification (RFID) technology to alleviate problems such as loss prevention and stock reduction. However, the research within this field is limited and fails to fully explore with depth, the wider network improvements that can be made to optimize the supply chain through efficient RTE management. This paper, investigates the nature of RTE network management building on current research and practices, filling a gap in the literature, through the investigation of a product-centric approach where the paradigms of “intelligent products” and “autonomous objects” are explored. A network optimizing approach with RTE management is explored, encouraging advanced research development of the RTE paradigm to align academic research with problematic areas in industry. Further research continues with the development of an agent-based software system, ready for application to a real-case study distribution network, producing quantitative results for further analysis. This is pivotal on the endeavor to developing agile support systems, fully utilizing an information-centric environment and encouraging RTE to be viewed as critical network optimizing tools rather than costly waste.
Resumo:
We develop a multi-agent based model to simulate a population which comprises of two ethnic groups and a peacekeeping force. We investigate the effects of different strategies for civilian movement to the resulting violence in this bi-communal population. Specifically, we compare and contrast random and race-based migration strategies. Race-based migration leads the formation of clusters. Previous work in this area has shown that same-race clustering instigates violent behavior in otherwise passive segments of the population. Our findings confirm this. Furthermore, we show that in settings where only one of the two races adopts race-based migration it is a winning strategy especially in violently predisposed populations. On the other hand, in relatively peaceful settings clustering is a restricting factor which causes the race that adopts it to drift into annihilation. Finally, we show that when race-based migration is adopted as a strategy by both ethnic groups it results in peaceful co-existence even in the most violently predisposed populations.
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This thesis challenges the consensual scholarly expectation of low EU impact in Central Asia. In particular, it claims that by focusing predominantly on narrow, micro-level factors, the prevailing theoretical perspectives risk overlooking less obvious aspects of the EU?s power, including structural aspects, and thus tend to underestimate the EU?s leverage in the region. Therefore, the thesis argues that a more structurally integrative and holistic approach is needed to understand the EU?s power in the region. In responding to this need, the thesis introduces a conceptual tool, which it terms „transnational power over? (TNPO). Inspired by debates in IPE, in particular new realist and critical IPE perspectives, and combining these views with insights from neorealist, neo-institutionalist and constructivist approaches to EU external relations, the concept of TNPO is an analytically eclectic notion, which helps to assess the degree to which, in today?s globalised and interdependent world, the EU?s power over third countries derives from its control over a combination of material, institutional and ideational structures, making it difficult for the EU?s partners to resist the EU?s initiatives or to reject its offers. In order to trace and assess the mechanisms of EU impact across these three structures, the thesis constructs a toolbox, which centres on four analytical distinctions: (i) EU-driven versus domestically driven mechanisms, (ii) mechanisms based on rationalist logics of action versus mechanisms following constructivist logics of action, (iii) agent-based versus purely structural mechanisms of TNPO, and (iv) transnational and intergovernmental mechanisms of EU impact. Using qualitative research methodology, the thesis then applies the conceptual model to the case of EU-Central Asia. It finds that the EU?s power over Central Asia effectively derives from its control over a combination of material, institutional and ideational structures, including its position as a leader in trade and investment in the region, its (geo)strategic and security-related capabilities vis-à-vis Central Asia, as well as the relatively dense level of institutionalisation of its relations with the five countries and the positive image of the EU in Central Asia as a more neutral actor.
Resumo:
The introduction of agent technology raises several security issues that are beyond conventional security mechanisms capability and considerations, but research in protecting the agent from malicious host attack is evolving. This research proposes two approaches to protecting an agent from being attacked by a malicious host. The first approach consists of an obfuscation algorithm that is able to protect the confidentiality of an agent and make it more difficult for a malicious host to spy on the agent. The algorithm uses multiple polynomial functions with multiple random inputs to convert an agent's critical data to a value that is meaningless to the malicious host. The effectiveness of the obfuscation algorithm is enhanced by addition of noise code. The second approach consists of a mechanism that is able to protect the integrity of the agent using state information, recorded during the agent execution process in a remote host environment, to detect a manipulation attack by a malicious host. Both approaches are implemented using a master-slave agent architecture that operates on a distributed migration pattern. Two sets of experimental test were conducted. The first set of experiments measures the migration and migration+computation overheads of the itinerary and distributed migration patterns. The second set of experiments is used to measure the security overhead of the proposed approaches. The protection of the agent is assessed by analysis of its effectiveness under known attacks. Finally, an agent-based application, known as Secure Flight Finder Agent-based System (SecureFAS) is developed, in order to prove the function of the proposed approaches.
Resumo:
We investigate the policies of (1) restricting social influence and (2) imposing curfews upon interacting citizens in a community. We compare and contrast their effects on the social order and the emerging levels of civil violence. Influence models have been used in the past in the context of decision making in a variety of application domains. The policy of curfews has been utilised with the aim of curbing social violence but little research has been done on its effectiveness. We develop a multi-agent-based model that is used to simulate a community of citizens and the police force that guards it. We find that restricting social influence does indeed pacify rebellious societies, but has the opposite effect on peaceful ones. On the other hand, our simple model indicates that restricting mobility through curfews has a pacifying effect across all types of society.
Resumo:
Wireless sensor networks have been identified as one of the key technologies for the 21st century. In order to overcome their limitations such as fault tolerance and conservation of energy, we propose a middleware solution, In-Motes. In-Motes stands as a fault tolerant platform for deploying and monitoring applications in real time offers a number of possibilities for the end user giving him in parallel the freedom to experiment with various parameters, in an effort the deployed applications to run in an energy efficient manner inside the network. The proposed scheme is evaluated through the In-Motes EYE application, aiming to test its merits under real time conditions. In-Motes EYE application which is an agent based real time In-Motes application developed for sensing acceleration variations in an environment. The application was tested in a prototype area, road alike, for a period of four months.
Resumo:
We present a stochastic agent-based model for the distribution of personal incomes in a developing economy. We start with the assumption that incomes are determined both by individual labour and by stochastic effects of trading and investment. The income from personal effort alone is distributed about a mean, while the income from trade, which may be positive or negative, is proportional to the trader's income. These assumptions lead to a Langevin model with multiplicative noise, from which we derive a Fokker-Planck (FP) equation for the income probability density function (IPDF) and its variation in time. We find that high earners have a power law income distribution while the low-income groups have a Levy IPDF. Comparing our analysis with the Indian survey data (obtained from the world bank website: http://go.worldbank.org/SWGZB45DN0) taken over many years we obtain a near-perfect data collapse onto our model's equilibrium IPDF. Using survey data to relate the IPDF to actual food consumption we define a poverty index (Sen A. K., Econometrica., 44 (1976) 219; Kakwani N. C., Econometrica, 48 (1980) 437), which is consistent with traditional indices, but independent of an arbitrarily chosen "poverty line" and therefore less susceptible to manipulation. Copyright © EPLA, 2010.
Resumo:
This study investigates the critical role that opinion leaders (or influentials) play in the adoption process of new products. Recent existing reseach evidence indicates a limited effect of opinion leaders on diffusion processes, yet these studies take into account merely the network position of opinion leaders without addressing their influential power. Empirical findings of our study show that opinion leaders, in addition to having a more central network position, possess more accurate knowledge about a product and tend to be less susceptible to norms and more innovative. Experiments that address these attributes, using an agent-based model, demonstrate that opinion leaders increase the speed of the information stream and the adoption process itself. Furthermore, they increase the maximum adoption percentage. These results indicate that targeting opinion leaders remains a valuable marketing strategy.
Resumo:
Simulation is an effective method for improving supply chain performance. However, there is limited advice available to assist practitioners in selecting the most appropriate method for a given problem. Much of the advice that does exist relies on custom and practice rather than a rigorous conceptual or empirical analysis. An analysis of the different modelling techniques applied in the supply chain domain was conducted, and the three main approaches to simulation used were identified; these are System Dynamics (SD), Discrete Event Simulation (DES) and Agent Based Modelling (ABM). This research has examined these approaches in two stages. Firstly, a first principles analysis was carried out in order to challenge the received wisdom about their strengths and weaknesses and a series of propositions were developed from this initial analysis. The second stage was to use the case study approach to test these propositions and to provide further empirical evidence to support their comparison. The contributions of this research are both in terms of knowledge and practice. In terms of knowledge, this research is the first holistic cross paradigm comparison of the three main approaches in the supply chain domain. Case studies have involved building ‘back to back’ models of the same supply chain problem using SD and a discrete approach (either DES or ABM). This has led to contributions concerning the limitations of applying SD to operational problem types. SD has also been found to have risks when applied to strategic and policy problems. Discrete methods have been found to have potential for exploring strategic problem types. It has been found that discrete simulation methods can model material and information feedback successfully. Further insights have been gained into the relationship between modelling purpose and modelling approach. In terms of practice, the findings have been summarised in the form of a framework linking modelling purpose, problem characteristics and simulation approach.
Resumo:
The supply chain can be a source of competitive advantage for the firm. Simulation is an effective tool for investigating supply chain problems. The three main simulation approaches in the supply chain context are System Dynamics (SD), Discrete Event Simulation (DES) and Agent Based Modelling (ABM). A sample from the literature suggests that whilst SD and ABM have been used to address strategic and planning problems, DES has mainly been used on planning and operational problems., A review of received wisdom suggests that historically, driven by custom and practice, certain simulation techniques have been focused on certain problem types. A theoretical review of the techniques, however, suggests that the scope of their application should be much wider and that supply chain practitioners could benefit from applying them in this broader way.