827 resultados para artifical intelligence


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All intelligence relies on search --- for example, the search for an intelligent agent's next action. Search is only likely to succeed in resource-bounded agents if they have already been biased towards finding the right answer. In artificial agents, the primary source of bias is engineering. This dissertation describes an approach, Behavior-Oriented Design (BOD) for engineering complex agents. A complex agent is one that must arbitrate between potentially conflicting goals or behaviors. Behavior-oriented design builds on work in behavior-based and hybrid architectures for agents, and the object oriented approach to software engineering. The primary contributions of this dissertation are: 1.The BOD architecture: a modular architecture with each module providing specialized representations to facilitate learning. This includes one pre-specified module and representation for action selection or behavior arbitration. The specialized representation underlying BOD action selection is Parallel-rooted, Ordered, Slip-stack Hierarchical (POSH) reactive plans. 2.The BOD development process: an iterative process that alternately scales the agent's capabilities then optimizes the agent for simplicity, exploiting tradeoffs between the component representations. This ongoing process for controlling complexity not only provides bias for the behaving agent, but also facilitates its maintenance and extendibility. The secondary contributions of this dissertation include two implementations of POSH action selection, a procedure for identifying useful idioms in agent architectures and using them to distribute knowledge across agent paradigms, several examples of applying BOD idioms to established architectures, an analysis and comparison of the attributes and design trends of a large number of agent architectures, a comparison of biological (particularly mammalian) intelligence to artificial agent architectures, a novel model of primate transitive inference, and many other examples of BOD agents and BOD development.

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Most Artificial Intelligence (AI) work can be characterized as either ``high-level'' (e.g., logical, symbolic) or ``low-level'' (e.g., connectionist networks, behavior-based robotics). Each approach suffers from particular drawbacks. High-level AI uses abstractions that often have no relation to the way real, biological brains work. Low-level AI, on the other hand, tends to lack the powerful abstractions that are needed to express complex structures and relationships. I have tried to combine the best features of both approaches, by building a set of programming abstractions defined in terms of simple, biologically plausible components. At the ``ground level'', I define a primitive, perceptron-like computational unit. I then show how more abstract computational units may be implemented in terms of the primitive units, and show the utility of the abstract units in sample networks. The new units make it possible to build networks using concepts such as long-term memories, short-term memories, and frames. As a demonstration of these abstractions, I have implemented a simulator for ``creatures'' controlled by a network of abstract units. The creatures exist in a simple 2D world, and exhibit behaviors such as catching mobile prey and sorting colored blocks into matching boxes. This program demonstrates that it is possible to build systems that can interact effectively with a dynamic physical environment, yet use symbolic representations to control aspects of their behavior.

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This report outlines the problem of intelligent failure recovery in a problem-solver for electrical design. We want our problem solver to learn as much as it can from its mistakes. Thus we cast the engineering design process on terms of Problem Solving by Debugging Almost-Right Plans, a paradigm for automatic problem solving based on the belief that creation and removal of "bugs" is an unavoidable part of the process of solving a complex problem. The process of localization and removal of bugs called for by the PSBDARP theory requires an approach to engineering analysis in which every result has a justification which describes the exact set of assumptions it depends upon. We have developed a program based on Analysis by Propagation of Constraints which can explain the basis of its deductions. In addition to being useful to a PSBDARP designer, these justifications are used in Dependency-Directed Backtracking to limit the combinatorial search in the analysis routines. Although the research we will describe is explicitly about electrical circuits, we believe that similar principles and methods are employed by other kinds of engineers, including computer programmers.

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El projecte tracte d' implementar una solució de Business Intelligence sota la plataforma Microsoft.Aquest projecte va destinat al Departament de Comptabilitat de l' Ajuntament de Cambrils, i està relacionat amb la funció del control de les despeses i els ingressos

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Resumen tomado de la publicaci??n

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Engineering of negotiation model allows to develop effective heuristic for business intelligence. Digital ecosystems demand open negotiation models. To define in advance effective heuristics is not compliant with the requirement of openness. The new challenge is to develop business intelligence in advance exploiting an adaptive approach. The idea is to learn business strategy once new negotiation model rise in the e-market arena. In this paper we present how recommendation technology may be deployed in an open negotiation environment where the interaction protocol models are not known in advance. The solution we propose is delivered as part of the ONE Platform, open source software that implements a fully distributed open environment for business negotiation

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Pearon's resource from the Brookshear Chapter

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La globalización y la competitividad como realidad de las empresas, implica que los gerentes preparen a sus empresas de la mejor manera para sobrevivir en este mundo tan inestable y cambiante. El primer paso consta de investigar y medir como se encuentra la empresa en cada uno de sus componentes, tales como recurso humano, mercadeo, logística, operación y por último y más importante las finanzas. El conocimiento de salud financiera y de los riesgos asociados a la actividad de las empresas, les permitirá a los gerentes tomar las decisiones correctas para ser rentables y perdurables en el mundo de los negocios inmerso en la globalización y competitividad. Esta apreciación es pertinente en Avianca S.A. esto teniendo en cuenta su progreso y evolución desde su primer vuelo el 5 de diciembre de 1919 comercial, hasta hoy cuando cotiza en la bolsa de Nueva York. Se realizó un análisis de tipo descriptivo, acompañado de la aplicación de ratios y nomenclaturas, dando lugar a establecer la salud financiera y los riesgos, no solo de Avianca sino también del sector aeronáutico. Como resultado se obtuvo que el sector aeronáutico sea financieramente saludable en el corto plazo, pero en el largo plazo su salud financiera se ve comprometida por los riegos asociados al sector y a la actividad desarrollada.

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Adaptar los tests de inteligencia WISC para poder evaluar as?? al individuo con respecto al grupo seg??n las habilidades valoradas en cada cultura. Reajustar el WISC a la cultura catalana; hasta ahora los tests eran castellanos y hace falta adaptarlos al entorno para que sean realmente efectivos. 413 ni??os de 16 escuelas escogidas al azar. Edad entre 6 y 12 a??os. An??lisis exhaustivo de la prueba de Wechsler y de la adaptaci??n TEA, revisi??n cr??tica y adaptaci??n catalana. Prueba piloto para cotejar la eficiencia. Correcci??n de la WISC creada a partir de las divergencias estad??sticas entre el standard y los resultados de la prueba piloto. Encuestas, Test de WISC original y adaptado, muestreo. Tablas, an??lisis estad??sticos de correlaci??n, an??lisis factorial, fiabilidad y baremos de tipificaci??n. Se ha conseguido obtener un test WISC mucho m??s adaptado a la realidad de Catalunya gracias a la eliminaci??n de errores y dificultades que generaban las versiones Wechsler y TEA anteriores.

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Manual diseñado para que profesores de enseñanza secundaria ayuden y apoyen el desarrollo de la inteligencia emocional, que abarca la conciencia y la responsabilidad, la actitud positiva y apreciativa, la empatía y el respeto, la motivación y la persistencia. Las actividades para nueve sesiones desarrollan la inteligencia con respecto a uno mismo, otras personas, el empleo y el futuro.

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El autor se basa en las inteligencias múltiples para explicar cómo la inteligencia práctica es una habilidad clave de la vida y ofrece una estructura conceptual para definir y describir el sentido común. Expone cómo las personas con inteligencia práctica pueden emplear los conocimientos lingüísticos para adoptar hábitos de lenguaje semánticamente buenos, tomar decisiones mejores, pensar en términos de opciones y posibilidades, aceptar la ambigüedad y la complejidad, articular problemas con claridad y trabajar a través de soluciones. Muestra que las habilidades de inteligencia práctica se pueden mejorar con la educación y el entrenamiento adecuado y desafía a todos para mejorar sus destrezas y ayudar a otros a desarrollar sus propias capacidades de inteligencia práctica.