939 resultados para State-based reasoning


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Este artigo apresenta o caso do modelo de mensura????o de desempenho existente na Secretaria de Estado da Fazenda do Rio Grande do Sul. Mediante abordagem explorat??ria e descritiva, baseada em entrevistas em profundidade, comparamos as similaridades entre o modelo vigente na Secretaria e as principais caracter??sticas citadas nos estudos desses modelos aplicados ?? iniciativa privada. Encontramos como semelhan??as: a dissocia????o entre recompensa e esfor??o; negocia????o de metas; e mecanismos sociais de puni????o. A an??lise das s??ries trimestrais dos indicadores de desempenho, na compara????o meta/realizado entre 2005-2008 (14 trimestres, at?? junho/2008), fornece evid??ncias iniciais de que os funcion??rios da Secretaria t??m atingido em m??dia 91,46% das metas. Isso sugere a exist??ncia de folga or??ament??ria e, portanto, de baixo incentivo ao desempenho.

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Este estudo foi realizado em três marcenarias no sul do Estado do Espírito Santo, com o objetivo de analisar o layout e propor mudanças que otimizem o funcionamento harmônico entre o local de trabalho e o trabalhador, considerando-se fatores ergonômicos, fluxo de produção e produtividade. A coleta de dados foi feita analisando-se as condições do ambiente de trabalho (clima, ruído, iluminação) e aplicando uma entrevista para avaliar as condições gerais e de segurança no trabalho. O layout foi avaliado por medições, observação da sequência de trabalho nas máquinas e aplicação do software AutoCAD 2000. Os resultados indicaram que o Índice de Bulbo Úmido e o Termômetro de Globo estavam de acordo com a Norma Regulamentadora nº 15 (atividade moderada), sendo de 26,38 ºC, em média. Os níveis médios de ruído foram de 87,48 dB (A), acima do permitido para uma jornada de 8 h diárias (NR 15). A luminosidade média, encontrada em duas marcenarias, ficou acima da faixa de iluminação mínima recomendada para esse trabalho de maquinarias (NBR 5413/92). Todas as marcenarias tinham disposição desordenada do maquinário em razão da sequência lógica de trabalho, presença de pilastras e resíduos na área útil e de passagem, piso desnivelado, falta de rampas para acesso aos galpões, manutenção de máquinas e equipamentos de forma incorreta, falhas no telhado e ausência de bancadas para facilitar a adoção de uma melhor postura durante o manuseio das peças.

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O número de municípios infestados pelo Aedes aegypti no Estado do Espírito Santo vem aumentando gradativamente, levando a altas taxas de incidência de dengue ao longo dos anos. Apesar das tentativas de combate à doença, esta se tornou uma das maiores preocupações na saúde pública do Estado. Este estudo se propõe a descrever a dinâmica da expansão da doença no Estado a partir da associação entre variáveis ambientais e populacionais, utilizando dados operacionalizados por meio de técnicas de geoprocessamento. O estudo utilizou como fonte de dados a infestação pelo mosquito vetor e o coeficiente de incidência da doença, as distâncias rodoviárias intermunicipais do Estado, a altitude dos municípios e as variáveis geoclimáticas (temperatura e suficiência de água), incorporadas a uma ferramenta operacional, as Unidades Naturais do Espírito Santo (UNES), representadas em um único mapa operacionalizado em Sistema de Informação Geográfica (SIG), obtido a partir do Sistema Integrado de Bases Georreferenciadas do Estado do Espírito Santo. Para análise dos dados, foi realizada a Regressão de Poisson para os dados de incidência de dengue e Regressão Logística para os de infestação pelo vetor. Em seguida, os dados de infestação pelo mosquito e incidência de dengue foram georreferenciados, utilizando como ferramenta operacional o SIG ArcGIS versão 9.2. Observou-se que a pluviosidade é um fator que contribui para o surgimento de mosquito em áreas não infestadas. Altas temperaturas contribuem para um alto coeficiente de incidência de dengue nos municípios capixabas. A variável distância em relação a municípios populosos é um fator de proteção para a incidência da doença. A grande variabilidade encontrada nos dados, que não é explicada pelas variáveis utilizadas no modelo para incidência da doença, reforça a premissa de que a dengue é condicionada pela interação dinâmica entre muitas variáveis que o estudo não abordou. A espacialização dos dados de infestação pelo mosquito e incidência de dengue e as Zonas Naturais do ES permitiu a visualização da influência das variáveis estatisticamente significantes nos modelos utilizados no padrão da introdução e disseminação da doença no Estado.

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A novel approach to scheduling resolution by combining Autonomic Computing (AC), Multi-Agent Systems (MAS), Case-based Reasoning (CBR), and Bio-Inspired Optimization Techniques (BIT) will be described. AC has emerged as a paradigm aiming at incorporating applications with a management structure similar to the central nervous system. The main intentions are to improve resource utilization and service quality. In this paper we envisage the use of MAS paradigm for supporting dynamic and distributed scheduling in Manufacturing Systems with AC properties, in order to reduce the complexity of managing manufacturing systems and human interference. The proposed CBR based Intelligent Scheduling System was evaluated under different dynamic manufacturing scenarios.

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The scheduling problem is considered in complexity theory as a NP-hard combinatorial optimization problem. Meta-heuristics proved to be very useful in the resolution of this class of problems. However, these techniques require parameter tuning which is a very hard task to perform. A Case-based Reasoning module is proposed in order to solve the parameter tuning problem in a Multi-Agent Scheduling System. A computational study is performed in order to evaluate the proposed CBR module performance.

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This paper addresses the problem of Biological Inspired Optimization Techniques (BIT) parameterization, considering the importance of this issue in the design of BIT especially when considering real world situations, subject to external perturbations. A learning module with the objective to permit a Multi-Agent Scheduling System to automatically select a Meta-heuristic and its parameterization to use in the optimization process is proposed. For the learning process, Casebased Reasoning was used, allowing the system to learn from experience, in the resolution of similar problems. Analyzing the obtained results we conclude about the advantages of its use.

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In this paper, we foresee the use of Multi-Agent Systems for supporting dynamic and distributed scheduling in Manufacturing Systems. We also envisage the use of Autonomic properties in order to reduce the complexity of managing systems and human interference. By combining Multi-Agent Systems, Autonomic Computing, and Nature Inspired Techniques we propose an approach for the resolution of dynamic scheduling problem, with Case-based Reasoning Learning capabilities. The objective is to permit a system to be able to automatically adopt/select a Meta-heuristic and respective parameterization considering scheduling characteristics. From the comparison of the obtained results with previous results, we conclude about the benefits of its use.

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A key aspect of decision-making in a disaster response scenario is the capability to evaluate multiple and simultaneously perceived goals. Current competing approaches to build decision-making agents are either mental-state based as BDI, or founded on decision-theoretic models as MDP. The BDI chooses heuristically among several goals and the MDP searches for a policy to achieve a specific goal. In this paper we develop a preferences model to decide among multiple simultaneous goals. We propose a pattern, which follows a decision-theoretic approach, to evaluate the expected causal effects of the observable and non-observable aspects that inform each decision. We focus on yes-or-no (i.e., pursue or ignore a goal) decisions and illustrate the proposal using the RoboCupRescue simulation environment.

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Inorganica Chimica Acta 356 (2003) 215-221

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Recent changes in electricity markets (EMs) have been potentiating the globalization of distributed generation. With distributed generation the number of players acting in the EMs and connected to the main grid has grown, increasing the market complexity. Multi-agent simulation arises as an interesting way of analysing players’ behaviour and interactions, namely coalitions of players, as well as their effects on the market. MASCEM was developed to allow studying the market operation of several different players and MASGriP is being developed to allow the simulation of the micro and smart grid concepts in very different scenarios This paper presents a methodology based on artificial intelligence techniques (AI) for the management of a micro grid. The use of fuzzy logic is proposed for the analysis of the agent consumption elasticity, while a case based reasoning, used to predict agents’ reaction to price changes, is an interesting tool for the micro grid operator.

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Dissertação apresentada para obtenção do Grau de Doutor em Sistemas de Informação Industriais, Engenharia Electrotécnica, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

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In the recent past, hardly anyone could predict this course of GIS development. GIS is moving from desktop to cloud. Web 2.0 enabled people to input data into web. These data are becoming increasingly geolocated. Big amounts of data formed something that is called "Big Data". Scientists still don't know how to deal with it completely. Different Data Mining tools are used for trying to extract some useful information from this Big Data. In our study, we also deal with one part of these data - User Generated Geographic Content (UGGC). The Panoramio initiative allows people to upload photos and describe them with tags. These photos are geolocated, which means that they have exact location on the Earth's surface according to a certain spatial reference system. By using Data Mining tools, we are trying to answer if it is possible to extract land use information from Panoramio photo tags. Also, we tried to answer to what extent this information could be accurate. At the end, we compared different Data Mining methods in order to distinguish which one has the most suited performances for this kind of data, which is text. Our answers are quite encouraging. With more than 70% of accuracy, we proved that extracting land use information is possible to some extent. Also, we found Memory Based Reasoning (MBR) method the most suitable method for this kind of data in all cases.

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Machine ethics is an interdisciplinary field of inquiry that emerges from the need of imbuing autonomous agents with the capacity of moral decision-making. While some approaches provide implementations in Logic Programming (LP) systems, they have not exploited LP-based reasoning features that appear essential for moral reasoning. This PhD thesis aims at investigating further the appropriateness of LP, notably a combination of LP-based reasoning features, including techniques available in LP systems, to machine ethics. Moral facets, as studied in moral philosophy and psychology, that are amenable to computational modeling are identified, and mapped to appropriate LP concepts for representing and reasoning about them. The main contributions of the thesis are twofold. First, novel approaches are proposed for employing tabling in contextual abduction and updating – individually and combined – plus a LP approach of counterfactual reasoning; the latter being implemented on top of the aforementioned combined abduction and updating technique with tabling. They are all important to model various issues of the aforementioned moral facets. Second, a variety of LP-based reasoning features are applied to model the identified moral facets, through moral examples taken off-the-shelf from the morality literature. These applications include: (1) Modeling moral permissibility according to the Doctrines of Double Effect (DDE) and Triple Effect (DTE), demonstrating deontological and utilitarian judgments via integrity constraints (in abduction) and preferences over abductive scenarios; (2) Modeling moral reasoning under uncertainty of actions, via abduction and probabilistic LP; (3) Modeling moral updating (that allows other – possibly overriding – moral rules to be adopted by an agent, on top of those it currently follows) via the integration of tabling in contextual abduction and updating; and (4) Modeling moral permissibility and its justification via counterfactuals, where counterfactuals are used for formulating DDE.

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Dissertação de mestrado em Direito das Crianças, Família e Sucessões

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This paper discusses how object-oriented iuheritance can be re-interpreted if statecharts are used for modelling the dynamic behaviour of an object. The support of inheritance of statecharts allows the improvement of systems' development by easing the reutilization of parts of already developed euccessful systems, aad by promoting the iterative and continuous models' refinement advocated by the operatioaal approach. Statechart is the formalism used within UML to specify reactive state.based behaviours. This paper covers the use of statecharts within the modelling of embedded systems for industrial control applxications, where performance and memory usage are main concerns.