821 resultados para distributed programming abstractions


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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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In this paper, we introduce a DAI approach called hereinafter Fuzzy Distributed Artificial Intelligence (FDAI). Through the use of fuzzy logic, we have been able to develop mechanisms that we feel may effectively improve current DAI systems, giving much more flexibility and providing the subsidies which a formal theory can bring. The appropriateness of the FDAI approach is explored in an important application, a fuzzy distributed traffic-light control system, where we have been able to aggregate and study several issues concerned with fuzzy and distributed artificial intelligence. We also present a number of current research directions necessary to develop the FDAI approach more fully.

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We discuss non-steady state electrical characteristics of a metal-insulator-metal structure. We consider an exponential distribution (in energy) of impurity states in addition to impurity states at a single energy level within the depletion region. We discuss thermal as well as isothermal characteristics and present an expression for the temperature of maximum current (Tm) and a method to calculate the density of exponentially distributed impurity states. We plot the theoretical curves for various sets of parameters and the variation of Tm, and Im (maximum current) with applied potential for various impurity distributions. The present model can explain the available experimental results. Finally we compare the non-steady state characteristics in three cases: (i) impurity states only at a single energy level, (ii) uniform energetic distribution of impurity states, and (iii) exponential energetic distribution of impurity states.

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The task of controlling urban traffic requires flexibility, adaptability and handling uncertain information spread through the intersection network. The use of fuzzy sets concepts convey these characteristics to improve system performance. This paper reviews a distributed traffic control system built upon a fuzzy distributed architecture previously developed by the authors. The emphasis of the paper is on the application of the system to control part of Campinas downtown area. Simulation experiments considering several traffic scenarios were performed to verify the capabilities of the system in controlling a set of coupled intersections. The performance of the proposed system is compared with conventional traffic control strategies under the same scenarios. The results obtained show that the distributed traffic control system outperforms conventional systems as far as average queues, average delay and maximum delay measures are concerned.

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The increase of computing power of the microcomputers has stimulated the building of direct manipulation interfaces that allow graphical representation of Linear Programming (LP) models. This work discusses the components of such a graphical interface as the basis for a system to assist users in the process of formulating LP problems. In essence, this work proposes a methodology which considers the modelling task as divided into three stages which are specification of the Data Model, the Conceptual Model and the LP Model. The necessity for using Artificial Intelligence techniques in the problem conceptualisation and to help the model formulation task is illustrated.

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In this paper, we consider a vector optimization problem where all functions involved are defined on Banach spaces. We obtain necessary and sufficient criteria for optimality in the form of Karush-Kuhn-Tucker conditions. We also introduce a nonsmooth dual problem and provide duality theorems.

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This article presents the implementation of a distributed system of virtual reality, through the integration of services offered by the CORBA platform (Common Object Request Broker Architecture) and by the environment of development of 3D graphic applications in real time, the WorldToolkit, of Sense8. The developed application for the validation of this integration is that of a virtual city, with an emphasis on its traffic ways, vehicles (movable objects) and buildings (immovable objects). In this virtual world, several users can interact, each one controlling his/her own car. Since the modelling of the application took into consideration the criteria and principles of the Transport Engineering, the aim is to use it in the planning, project and construction of traffic ways for vehicles. The system was structured according to the approach client/server utilizing multicast communication among the participating nodes. The chosen implementation for the CORBA was the Iona's ORBIX software. The performance results obtained are presented and discussed in the end.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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A combined methodology consisting of successive linear programming (SLP) and a simple genetic algorithm (SGA) solves the reactive planning problem. The problem is divided into operating and planning subproblems; the operating subproblem, which is a nonlinear, ill-conditioned and nonconvex problem, consists of determining the voltage control and the adjustment of reactive sources. The planning subproblem consists of obtaining the optimal reactive source expansion considering operational, economical and physical characteristics of the system. SLP solves the optimal reactive dispatch problem related to real variables, while SGA is used to determine the necessary adjustments of both the binary and discrete variables existing in the modelling problem. Once the set of candidate busbars has been defined, the program implemented gives the location and size of the reactive sources needed, if any, to maintain the operating and security constraints.

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Mathematical programming problems with equilibrium constraints (MPEC) are nonlinear programming problems where the constraints have a form that is analogous to first-order optimality conditions of constrained optimization. We prove that, under reasonable sufficient conditions, stationary points of the sum of squares of the constraints are feasible points of the MPEC. In usual formulations of MPEC all the feasible points are nonregular in the sense that they do not satisfy the Mangasarian-Fromovitz constraint qualification of nonlinear programming. Therefore, all the feasible points satisfy the classical Fritz-John necessary optimality conditions. In principle, this can cause serious difficulties for nonlinear programming algorithms applied to MPEC. However, we show that most feasible points do not satisfy a recently introduced stronger optimality condition for nonlinear programming. This is the reason why, in general, nonlinear programming algorithms are successful when applied to MPEC.