874 resultados para AGENT
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This work proposes an animated pedagogical agent that has the role of providing emotional support to the student: motivating and encouraging him, making him believe in his self-ability, and promoting a positive mood in him, which fosters learning. This careful support of the agent, its affective tactics, is expressed through emotional behaviour and encouragement messages of the lifelike character. Due to human social tendency of anthropomorphising software, we believe that a software agent can accomplish this affective role. In order to choose the adequate affective tactics, the agent should also know the student’s emotions. The proposed agent recognises the student’s emotions: joy/distress, satisfaction/disappointment, anger/gratitude, and shame, from the student’s observable behaviour, i. e. his actions in the interface of the educational system. The inference of emotions is psychologically grounded on the cognitive theory of emotions. More specifically, we use the OCC model which is based on the cognitive approach of emotion and can be computationally implemented. Due to the dynamic nature of the student’s affective information, we adopted a BDI approach to implement the affective user model and the affective diagnosis. Besides, in our work we profit from the reasoning capacity of the BDI approach in order for the agent to deduce the student’s appraisal, which allows it to infer the student’s emotions. As a case study, the proposed agent is implemented as the Mediating Agent of MACES: an educational collaborative environment modelled as a multi-agent system and pedagogically based on the sociocultural theory of Vygotsky.
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A intenção deste trabalho é explorar dinâmicas de competição por meio de “simulação baseada em agentes”. Apoiando-se em um crescente número de estudos no campo da estratégia e teoria das organizações que utilizam métodos de simulação, desenvolveu-se um modelo computacional para simular situações de competição entre empresas e observar a eficiência relativa dos métodos de busca de melhoria de desempenho teorizados. O estudo também explora possíveis explicações para a persistência de desempenho superior ou inferior das empresas, associados às condições de vantagem ou desvantagem competitiva
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This thesis is comprised of three chapters. The first article studies the determinants of the labor force participation of elderly American males and investigates the factors that may account for the changes in retirement between 1950 and 2000. We develop a life-cycle general equilibrium model with endogenous retirement that embeds Social Security legislation and Medicare. Individuals are ex ante heterogeneous with respect to their preferences for leisure and face uncertainty about labor productivity, health status and out-of-pocket medical expenses. The model is calibrated to the U.S. economy in 2000 and is able to reproduce very closely the retirement behavior of the American population. It reproduces the peaks in the distribution of Social Security applications at ages 62 and 65 and the observed facts that low earners and unhealthy individuals retire earlier. It also matches very closely the increase in retirement from 1950 to 2000. Changes in Social Security policy - which became much more generous - and the introduction of Medicare account for most of the expansion of retirement. In contrast, the isolated impact of the increase in longevity was a delaying of retirement. In the second article, I develop an overlapping generations model of criminal behavior, which extends prior research on crime by taking into account individuals' labor supply decisions and the stigma effect that affects convicted offenders, lowering their likelihood of employment. I use the model to guide a quantitative assessment of the determinants of crime and of a counterfactual experiment in which an income redistribution policy is thought as an alternative to greater law enforcement. The model economy considered in this paper is populated by heterogeneous agents who live for a realistic number of periods, have preferences over consumption and leisure, and differ in terms of their age, their skills as well as their employment shocks. In addition, savings may be precautionary and allow partial insurance against the labor income shocks. Because of the lack of full insurance, this model generates an endogenous distribution of wealth across consumers, enabling us to assess the welfare implications of the redistribution policy experiment. I calibrated the model using the US data for 1980 and then use the model to investigate the changes in criminality between 1980 and 1996. The main results that come out of this study are: 1) Law enforcement policy was the most important factor behind the fall in criminality in the period, while the increase in inequality was the most important single factor promoting crime; 2) Stigmatization is not a free-cost crime control policy; 3) Income redistribution can be a powerful alternative policy to fight crime. Finally, the third article studies the impact of HIV/AIDS on per capita income and education. It explores two channels from HIV/AIDS to income that have not been sufficiently stressed by the literature: the reduction of the incentives to study due to shorter expected longevity and the reduction of productivity of experienced workers. In the model individuals live for three periods, may get infected in the second period and with some probability die of Aids before reaching the third period of their life. Parents care for the welfare of the future generations so that they will maximize lifetime utility of their dynasty. The simulations predict that the most affected countries in Sub-Saharan Africa will be in the future, on average, thirty percent poorer than they would be without AIDS. Schooling will decline in some cases by forty percent. These figures are dramatically reduced with widespread medical treatment, as it increases the survival probability and productivity of infected individuals.
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Starting from the idea that economic systems fall into complexity theory, where its many agents interact with each other without a central control and that these interactions are able to change the future behavior of the agents and the entire system, similar to a chaotic system we increase the model of Russo et al. (2014) to carry out three experiments focusing on the interaction between Banks and Firms in an artificial economy. The first experiment is relative to Relationship Banking where, according to the literature, the interaction over time between Banks and Firms are able to produce mutual benefits, mainly due to reduction of the information asymmetry between them. The following experiment is related to information heterogeneity in the credit market, where the larger the bank, the higher their visibility in the credit market, increasing the number of consult for new loans. Finally, the third experiment is about the effects on the credit market of the heterogeneity of prices that Firms faces in the goods market.
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Esta dissertação estuda a propagação de crises sobre o sistema financeiro. Mais especi- ficamente, busca-se desenvolver modelos que permitam simular como um determinado choque econômico atinge determinados agentes do sistema financeiro e apartir dele se propagam, transformando-se em um problema sistêmico. A dissertação é dividida em dois capítulos,além da introdução. O primeiro capítulo desenvolve um modelo de propa- gação de crises em fundos de investimento baseado em ciência das redes.Combinando dois modelos de propagação em redes financeiras, um simulando a propagação de perdas em redes bipartites de ativos e agentes financeiros e o outro simulando a propagação de perdas em uma rede de investimentos diretos em quotas de outros agentes, desenvolve-se um algoritmo para simular a propagação de perdas através de ambos os mecanismos e utiliza-se este algoritmo para simular uma crise no mercado brasileiro de fundos de investimento. No capítulo 2,desenvolve-se um modelo de simulação baseado em agentes, com agentes financeiros, para simular propagação de um choque que afeta o mercado de operações compromissadas.Criamos também um mercado artificial composto por bancos, hedge funds e fundos de curto prazo e simulamos a propagação de um choque de liquidez sobre um ativo de risco securitizando utilizado para colateralizar operações compromissadas dos bancos.
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Alternaria alternata, the causal agent of Alternaria brown spot (ABS), causes necrosis on leaves, twigs, and fruit, reducing the productivity and quality of fruits. Tangerines and their hybrids are highly susceptible to the disease. Species, hybrids, and cultivars of Citrus from the germplasm bank of the Estacao Experimental de Citricultura de Bebedouro, São Paulo, Brazil, were evaluated in 2004 and 2005 with respect to their resistance to A. alternata, both through natural infection and by inoculation. Detached leaves were also used to demonstrate susceptibility or resistance to the disease. Ten cultivars of Satsumas (Citrus unshiu), and 14 cultivars of Clementine mandarin (C. clementina) did not show any symptoms of the disease in their leaves, either through natural infection or when inoculated in the field. The Burguess SRA-412, Wallent SRA-438, Carvalhais, Ampefy SRA-459, Ananas SRA, and Macaque SRA-426 mandarin hybrids (C. reticulata) did not show symptoms of the disease under natural or artificial infection in the field. Some cultivars of C. deliciosa, C. tangerina, C. erythrosa, and C. temple showed symptoms of the disease, even though no previous record of their susceptibility to Alternaria brown spot had been previously reported. The hybrids Fairchild, Nova, Page, Fortune, and Sunburst were susceptible to the disease. However, Fremont mandarin (a crossing between C. clementina and C. reticulata), Encore (C. nobilis x C. deliciosa), and Fallglo (C. reticulata x C. paradisi) did not show symptoms in field, and few symptoms were verified in detached leaves. These materials are promising for the cultivation of tangerines, and will enable genetic improvement for the development of cultivars resistant to Alternaria brown spot. (c) 2007 Elsevier B.V. All rights reserved.
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Biofertilizers generated from the anaerobic and aerobic digestion of cattle manure, known as Bio1 and Bio2, respectively, were studied with regard to their microbial composition and effect on the mycelial growth of Phyllosticta citricarpa, the causal agent of citrus black spot (CBS). Two field experiments were conducted to determine the biofertilizer's potential (Bio1) in controlling CBS (2001/2002 and 2002/2003 crops). It was observed that the greatest number of microorganisms was found in the aerobically produced biofertilizer. Bio2 did not inhibit the mycelial growth of P. citricarpa. Mycelial growth of P. citricarpa was inversely proportional to the Bio1 biofertilizer concentration. In the 2001/2002 cropping season, the Biol effect in controlling CBS was directly proportional to its concentration, at the rate of 0 (healthy fruit), with R-2 = 0.88. Biol had a significant effect in controlling CBS, at a concentration of 10%, during the 2001/2002 cropping season, with DI values of 0.246 and 0.229 for the. 10 and 20% doses, respectively, compared to DI of 0.329 for the control. A directly proportional effect of the biofertilizer concentration on the percentage of fruits with a rating of zero was. also observed in the 2002/2003 cropping season, with R-2 = 0.48. However, even at doses higher than in the preceding cropping season, the biofertilizer was less effective, possibly due to a higher occurrence of the disease. Copper oxychloride and combined applications of copper oxychloride and carbendazim plus mancozeb controlled the disease. The possibility of using the biofertilizer as a protective biofungicide to replace copper oxychloride, especially in organic agriculture, should be explored. (c) 2005 Elsevier Ltd. All rights reserved.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Citrus black spot (CBS) is a fungal disease, caused by Guignardia citricarpa, that has a high economic impact on citrus. Although G. citricarpa has been associated with black spot of citrus, an adequate pathogenicity test is still not available. Thus, our objective was to develop and evaluate a simple, safe, and practical pathogenicity test. We used fruits from Pera-Rio and Valencia sweet orange trees from two different orchards, located in the State of São Paulo, Brazil. Inoculation was performed by placing six disks colonized by G. citricarpa, onto the peel of healthy fruits, previously bagged. In the Pera-Rio sweet orange grove, initial symptoms of the false melanose type resulting from the inoculations were observed 55 days after inoculation (dai). In the Valencia grove, initial symptoms also of the false melanose type resulting from the inoculations occurred 73 dai. A total of 92.8% and 86.6% of the Pera Rio and Valencia fruits inoculated, respectively, showed symptoms of CBS. Citrus black spot symptoms were not observed in any of the control fruits.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Pyrazinamide was condensed with the poly(ethylene glycol)-poly(aspartic acid) copolymer (PEG-PASP), a micelle-forming derivative was obtained that was characterized in terms of its critical micelle concentration (CMC) and micelle diameter. The CMC was found by observing the solubility of Sudan III in Poly(ethylene glycol)-poly(pyrazinamidomethyl aspartate) copolymer (PEG-PASP-PZA) solutions. The mean diameter of PEG-PASP-PZA micelles, obtained by analyzing the dynamic light-scattering data, was 78.2 nm. The PEG-PASP-PZA derivative, when assayed for anti-Mycobacterium activity, exhibited stronger activity than the simple drug.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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On-line learning methods have been applied successfully in multi-agent systems to achieve coordination among agents. Learning in multi-agent systems implies in a non-stationary scenario perceived by the agents, since the behavior of other agents may change as they simultaneously learn how to improve their actions. Non-stationary scenarios can be modeled as Markov Games, which can be solved using the Minimax-Q algorithm a combination of Q-learning (a Reinforcement Learning (RL) algorithm which directly learns an optimal control policy) and the Minimax algorithm. However, finding optimal control policies using any RL algorithm (Q-learning and Minimax-Q included) can be very time consuming. Trying to improve the learning time of Q-learning, we considered the QS-algorithm. in which a single experience can update more than a single action value by using a spreading function. In this paper, we contribute a Minimax-QS algorithm which combines the Minimax-Q algorithm and the QS-algorithm. We conduct a series of empirical evaluation of the algorithm in a simplified simulator of the soccer domain. We show that even using a very simple domain-dependent spreading function, the performance of the learning algorithm can be improved.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)