Lógica BDI fuzzy

Intendding to understand how the human mind operates, some philosophers and psycologists began to study about rationality. Theories were built from those studies and nowadays that interest have been extended to many other areas such as computing engineering and computing science, but with a minimal distinction at its goal: to understand the mind operational proccess and apply it on agents modelling to become possible the implementation (of softwares or hardwares) with the agent-oriented paradigm where agents are able to deliberate their own plans of actions. In computing science, the sub-area of multiagents systems has progressed using several works concerning artificial intelligence, computational logic, distributed systems, games theory and even philosophy and psycology. This present work hopes to show how it can be get a logical formalisation extention of a rational agents architecture model called BDI (based in a philosophic Bratman s Theory) in which agents are capable to deliberate actions from its beliefs, desires and intentions. The formalisation of this model is called BDI logic and it is a modal logic (in general it is a branching time logic) with three access relations: B, D and I. And here, it will show two possible extentions that tranform BDI logic in a modal-fuzzy logic where the formulae and the access relations can be evaluated by values from the interval [0,1]

Transaction scheduling using dynamic conflict avoidance

Software transaction memory (STM) systems have been used as an approach to improve performance, by allowing the concurrent execution of atomic blocks. However, under high-contention workloads, STM-based systems can considerably degrade performance, as transaction conflict rate increases. Contention management policies have been used as a way to select which transaction to abort when a conflict occurs. In general, contention managers are not capable of avoiding conflicts, as they can only select which transaction to abort and the moment it should restart. Since contention managers act only after a conflict is detected, it becomes harder to effectively increase transaction throughput. More proactive approaches have emerged, aiming at predicting when a transaction is likely to abort, postponing its execution. Nevertheless, most of the proposed proactive techniques are limited, as they do not replace the doomed transaction by another or, when they do, they rely on the operating system for that, having little or no control on which transaction to run. This article proposes LUTS, a lightweight user-level transaction scheduler. Unlike other techniques, LUTS provides the means for selecting another transaction to run in parallel, thus improving system throughput. We discuss LUTS design and propose a dynamic conflict-avoidance heuristic built around its scheduling capabilities. Experimental results, conducted with the STAMP and STMBench7 benchmark suites, running on TinySTM and SwissTM, show how our conflict-avoidance heuristic can effectively improve STM performance on high contention applications. © 2012 Springer Science+Business Media, LLC.

Sustainable urban energy planning: The case study of a tropical city

The urbanization of modern societies has imposed to the planners and decision-makers a more precise attention to facts not considered before. Several aspects, such as the energy availability and the deleterious effect of pollution on the populations, must be considered in the policy decisions of cities urbanization. The current paradigm presents centralized power stations supplying a city, and a combination of technologies may compose the energy mix of a country, such as thermal power plants, hydroelectric plants, wind systems and solar-based systems, with their corresponding emission pattern. A goal programming multi-objective optimization model is presented for the electric expansion analysis of a tropical city, and also a case study for the city of Guaratinguetá, Brazil, considering a particular wind and solar radiation patterns established according to actual data and modeled via the time series analysis method. Scenarios are proposed and the results of single environmental objective, single economic objective and goal programming multi-objective modeling are discussed. The consequences of each dispatch decision, which considers pollutant emission exportation to the neighborhood or the need of supplementing electricity by purchasing it from the public electric power grid, are discussed. The results revealed energetic dispatch for the alternatives studied and the optimum environmental and economic solution was obtained. © 2012 Elsevier Ltd.

Carregamento ótimo de veículos elétricos considerando as restrições das redes de distribuição de média tensão

Pós-graduação em Engenharia Elétrica - FEIS

Energy Management and Control for Islanded Microgrid Using Multi-Agents

This paper presents a multi-agent system for real-time operation of simulated microgrid using the Smart-Grid Test Bed at Washington State University. The multi-agent system (MAS) was developed in JADE (Java Agent DEvelopment Framework) which is a Foundation for Intelligent Physical Agents (FIPA) compliant open source multi-agent platform. The proposed operational strategy is mainly focused on using an appropriate energy management and control strategies to improve the operation of an islanded microgrid, formed by photovoltaic (PV) solar energy, batteries and resistive and rotating machines loads. The focus is on resource management and to avoid impact on loads from abrupt variations or interruption that changes the operating conditions. The management and control of the PV system is performed in JADE, while the microgrid model is simulated in RSCAD/RTDS (Real-Time Digital Simulator). Finally, the outcome of simulation studies demonstrated the feasibility of the proposed multi-agent approach for real-time operation of a microgrid.

Multi-planet extrasolar systems - detection and dynamics

20 years after the discovery of the first planets outside our solar system, the current exoplanetary population includes more than 700 confirmed planets around main sequence stars. Approximately 50% belong to multiple-planet systems in very diverse dynamical configurations, from two-planet hierarchical systems to multiple resonances that could only have been attained as the consequence of a smooth large-scale orbital migration. The first part of this paper reviews the main detection techniques employed for the detection and orbital characterization of multiple-planet systems, from the (now) classical radial velocity (RV) method to the use of transit time variations (TTV) for the identification of additional planetary bodies orbiting the same star. In the second part we discuss the dynamical evolution of multi-planet systems due to their mutual gravitational interactions. We analyze possible modes of motion for hierarchical, secular or resonant configurations, and what stability criteria can be defined in each case. In some cases, the dynamics can be well approximated by simple analytical expressions for the Hamiltonian function, while other configurations can only be studied with semi-analytical or numerical tools. In particular, we show how mean-motion resonances can generate complex structures in the phase space where different libration islands and circulation domains are separated by chaotic layers. In all cases we use real exoplanetary systems as working examples.

MAIA: an event-based modular architecture for intelligent agents

Online services are no longer isolated. The release of public APIs and technologies such as web hooks are allowing users and developers to access their information easily. Intelligent agents could use this information to provide a better user experience across services, connecting services with smart automatic. behaviours or actions. However, agent platforms are not prepared to easily add external sources such as web services, which hinders the usage of agents in the so-called Evented or Live Web. As a solution, this paper introduces an event-based architecture for agent systems, in accordance with the new tendencies in web programming. In particular, it is focused on personal agents that interact with several web services. With this architecture, called MAIA, connecting to new web services does not involve any modification in the platform.

Simulación eficiente de mecanismos flexibles mediante formulaciones topológicas

El objetivo de esta Tesis es presentar un método eficiente para la evaluación de sistemas multi-cuerpo con elementos flexibles con pequeñas deformaciones, basado en métodos topológicos para la simulación de sistemas tan complejos como los que se utilizan en la práctica y en tiempo real o próximo al real. Se ha puesto un especial énfasis en la resolución eficiente de aquellos aspectos que conllevan mayor coste computacional, tales como la evaluación de las ecuaciones dinámicas y el cálculo de los términos de inercia. Las ecuaciones dinámicas se establecen en función de las variables independientes del sistema, y la integración de las mismas se realiza mediante formulaciones implícitas de index-3. Esta Tesis se articula en seis Capítulos. En el Capítulo 1 se realiza una revisión bibliográfica de la simulación de sistemas flexibles y los métodos más relevantes de integración de las ecuaciones diferenciales del movimiento. Asimismo, se presentan los objetivos de esta Tesis. En el Capítulo 2 se presenta un método semi-recursivo para la evaluación de las ecuaciones de los sistemas multi-cuerpo con elementos flexibles basado en formulaciones topológicas y síntesis modal. Esta Tesis determina la posición de cada punto del cuerpo flexible en función de un sistema de referencia flotante que se mueve con dicho cuerpo y de las amplitudes de ciertos modos de deformación calculados a partir de un mallado obtenido mediante el Método de Elementos Finitos. Se presta especial atención en las condiciones de contorno que se han de tener en cuenta a la hora de establecer las variables que definen la deformación del cuerpo flexible. El Capítulo 3 se centra en la evaluación de los términos de inercia de los sistemas flexibles que generalmente conllevan un alto coste computacional. Se presenta un método que permite el cálculo de dichos términos basado en el uso de 24 matrices constantes que pueden ser calculadas previamente al proceso de integración. Estas matrices permiten evaluar la matriz de masas y el vector de fuerzas de inercia dependientes de la velocidad sin que sea necesario evaluar la posición deformada de todos los puntos del cuerpo flexible. Se realiza un análisis pormenorizado de dichas matrices con el objetivo de optimizar su cálculo estableciendo aproximaciones que permitan reducir el número de dichos términos y optimizar aún más su evaluación. Se analizan dos posibles simplificaciones: la primera utiliza una discretización no-consistente basada en elementos finitos en los que se definen únicamente los desplazamientos axiales de los nodos; en la segunda propuesta se hace uso de una matriz de masas concentradas (Lumped Mass). Basándose en la formulación presentada, el Capítulo 4 aborda la integración eficiente de las ecuaciones dinámicas. Se presenta un método iterativo para la integración con fórmulas de index-3 basado en la proyección de las ecuaciones dinámicas según las variables independientes del sistema multi-cuerpo. El cálculo del residuo del sistema de ecuaciones no lineales que se ha de resolver de modo iterativo se realiza mediante un proceso recursivo muy eficiente que aprovecha la estructura topológica del sistema. Se analizan tres formas de evaluar la matriz tangente del citado sistema no lineal: evaluación aproximada, numérica y recursiva. El método de integración presentado permite el uso de distintas fórmulas. En esta Tesis se analizan la Regla Trapezoidal, la fórmula BDF de segundo orden y un método híbrido TR-BDF2. Para este último caso se presenta un algoritmo de paso variable. En el Capítulo 5 plantea la implementación del método propuesto en un programa general de simulación de mecanismos que permita la resolución de cualquier sistema multi-cuerpo definiéndolo mediante un fichero de datos. La implementación de este programa se ha realizado tanto en C++ como en Java. Se muestran los resultados de las formulaciones presentadas en esta Tesis mediante la simulación de cuatro ejemplos de distinta complejidad. Mediante análisis concretos se comparan la formulación presentada con otras existentes. También se analiza el efecto del lenguaje de programación utilizado en la implementación y los efectos de las posibles simplificaciones planteadas. Por último, el Capítulo 6 resume las principales conclusiones alcanzadas en la Tesis y las futuras líneas de investigación que con ella se abren. ABSTRACT This Thesis presents an efficient method for solving the forward dynamics of a multi-body sys-tem formed by rigid and flexible bodies with small strains for real-time simulation of real-life models. It is based on topological formulations. The presented work focuses on the efficient solution of the most time-consuming tasks of the simulation process, such as the numerical integration of the motion differential equations and in particular the evaluation of the inertia terms corresponding to the flexible bodies. The dynamic equations are formulated in terms of independent variables of the muti-body system, and they are integrated by means of implicit index-3 formulae. The Thesis is arranged in six chapters. Chapter 1 presents a review of the most relevant and recent contributions related to the modelization of flexible multi-body systems and the integration of the corresponding dynamic equations. The main objectives of the Thesis are also presented in detail. Chapter 2 presents a semi-recursive method for solving the equations of a multi-body system with flexible bodies based on topological formulations and modal synthesis. This Thesis uses the floating frame approach and the modal amplitudes to define the position of any point at the flexible body. These modal deformed shapes are obtained by means of the Finite Element Method. Particular attention has been taken to the boundary conditions used to define the deformation of the flexible bodies. Chapter 3 focuses on the evaluation of the inertia terms, which is usually a very time-consuming task. A new method based on the use of 24 constant matrices is presented. These matrices are evaluated during the set-up step, before the integration process. They allow the calculation of the inertia terms in terms of the position and orientation of the local coordinate system and the deformation variables, and there is no need to evaluate the position and velocities of all the nodes of the FEM mesh. A deep analysis of the inertia terms is performed in order to optimize the evaluation process, reducing both the terms used and the number of arithmetic operations. Two possible simplifications are presented: the first one uses a non-consistent approach in order to define the inertia terms respect to the Cartesian coordinates of the FEM mesh, rejecting those corresponding to the angular rotations; the second approach makes use of lumped mass matrices. Based on the previously presented formulation, Chapter 4 is focused on the numerical integration of the motion differential equations. A new predictor-corrector method based on index-3 formulae and on the use of multi-body independent variables is presented. The evaluation of the dynamic equations in a new time step needs the solution of a set on nonlinear equations by a Newton-Raphson iterative process. The computation of the corresponding residual vector is performed efficiently by taking advantage of the system’s topological structure. Three methods to compute the tangent matrix are presented: an approximated evaluation that considers only the most relevant terms, a numerical approach based on finite differences and a recursive method that uses the topological structure. The method presented for integrating the dynamic equations can use a variety of integration formulae. This Thesis analyses the use of the trapezoidal rule, the 2nd order BDF formula and the hybrid TR-BDF2 method. A variable-time step strategy is presented for the last one. Chapter 5 describes the implementation of the proposed method in a general purpose pro-gram for solving any multibody defined by a data file. This program is implemented both in C++ and Java. Four examples are used to check the validity of the formulation and to compare this method with other methods commonly used to solve the dynamic equations of multi-body systems containing flexible bodies. The efficiency of the programming methodology used and the effect of the possible simplifications proposed are also analyzed. Chapter 6 summarizes the main Conclusions obtained in this Thesis and the new lines of research that have been opened.

Application of Agent Technology for Fault Diagnosis of Telecommunication Networks

La presente tesis doctoral contribuye al problema del diagnóstico autonómico de fallos en redes de telecomunicación. En las redes de telecomunicación actuales, las operadoras realizan tareas de diagnóstico de forma manual. Dichas operaciones deben ser llevadas a cabo por ingenieros altamente cualificados que cada vez tienen más dificultades a la hora de gestionar debidamente el crecimiento exponencial de la red tanto en tamaño, complejidad y heterogeneidad. Además, el advenimiento del Internet del Futuro hace que la demanda de sistemas que simplifiquen y automaticen la gestión de las redes de telecomunicación se haya incrementado en los últimos años. Para extraer el conocimiento necesario para desarrollar las soluciones propuestas y facilitar su adopción por los operadores de red, se propone una metodología de pruebas de aceptación para sistemas multi-agente enfocada en simplificar la comunicación entre los diferentes grupos de trabajo involucrados en todo proyecto de desarrollo software: clientes y desarrolladores. Para contribuir a la solución del problema del diagnóstico autonómico de fallos, se propone una arquitectura de agente capaz de diagnosticar fallos en redes de telecomunicación de manera autónoma. Dicha arquitectura extiende el modelo de agente Belief-Desire- Intention (BDI) con diferentes modelos de diagnóstico que gestionan las diferentes sub-tareas del proceso. La arquitectura propuesta combina diferentes técnicas de razonamiento para alcanzar su propósito gracias a un modelo estructural de la red, que usa razonamiento basado en ontologías, y un modelo causal de fallos, que usa razonamiento Bayesiano para gestionar debidamente la incertidumbre del proceso de diagnóstico. Para asegurar la adecuación de la arquitectura propuesta en situaciones de gran complejidad y heterogeneidad, se propone un marco de argumentación que permite diagnosticar a agentes que estén ejecutando en dominios federados. Para la aplicación de este marco en un sistema multi-agente, se propone un protocolo de coordinación en el que los agentes dialogan hasta alcanzar una conclusión para un caso de diagnóstico concreto. Como trabajos futuros, se consideran la extensión de la arquitectura para abordar otros problemas de gestión como el auto-descubrimiento o la auto-optimización, el uso de técnicas de reputación dentro del marco de argumentación para mejorar la extensibilidad del sistema de diagnóstico en entornos federados y la aplicación de las arquitecturas propuestas en las arquitecturas de red emergentes, como SDN, que ofrecen mayor capacidad de interacción con la red. ABSTRACT This PhD thesis contributes to the problem of autonomic fault diagnosis of telecommunication networks. Nowadays, in telecommunication networks, operators perform manual diagnosis tasks. Those operations must be carried out by high skilled network engineers which have increasing difficulties to properly manage the growing of those networks, both in size, complexity and heterogeneity. Moreover, the advent of the Future Internet makes the demand of solutions which simplifies and automates the telecommunication network management has been increased in recent years. To collect the domain knowledge required to developed the proposed solutions and to simplify its adoption by the operators, an agile testing methodology is defined for multiagent systems. This methodology is focused on the communication gap between the different work groups involved in any software development project, stakeholders and developers. To contribute to overcoming the problem of autonomic fault diagnosis, an agent architecture for fault diagnosis of telecommunication networks is defined. That architecture extends the Belief-Desire-Intention (BDI) agent model with different diagnostic models which handle the different subtasks of the process. The proposed architecture combines different reasoning techniques to achieve its objective using a structural model of the network, which uses ontology-based reasoning, and a causal model, which uses Bayesian reasoning to properly handle the uncertainty of the diagnosis process. To ensure the suitability of the proposed architecture in complex and heterogeneous environments, an argumentation framework is defined. This framework allows agents to perform fault diagnosis in federated domains. To apply this framework in a multi-agent system, a coordination protocol is defined. This protocol is used by agents to dialogue until a reliable conclusion for a specific diagnosis case is reached. Future work comprises the further extension of the agent architecture to approach other managements problems, such as self-discovery or self-optimisation; the application of reputation techniques in the argumentation framework to improve the extensibility of the diagnostic system in federated domains; and the application of the proposed agent architecture in emergent networking architectures, such as SDN, which offers new capabilities of control for the network.

Neutrosophic and Modal Components of Relations in Complex Systems

Semiotic components in the relations of complex systems depend on the Subject. There are two main semiotic components: Neutrosophic and Modal. Modal components are alethical and deontical. In this paper the authors applied the theory of Neutrosophy and Modal Logic to Deontical Impure Systems.

A formal framework for modelling complex network management systems

Society today is completely dependent on computer networks, the Internet and distributed systems, which place at our disposal the necessary services to perform our daily tasks. Subconsciously, we rely increasingly on network management systems. These systems allow us to, in general, maintain, manage, configure, scale, adapt, modify, edit, protect, and enhance the main distributed systems. Their role is secondary and is unknown and transparent to the users. They provide the necessary support to maintain the distributed systems whose services we use every day. If we do not consider network management systems during the development stage of distributed systems, then there could be serious consequences or even total failures in the development of the distributed system. It is necessary, therefore, to consider the management of the systems within the design of the distributed systems and to systematise their design to minimise the impact of network management in distributed systems projects. In this paper, we present a framework that allows the design of network management systems systematically. To accomplish this goal, formal modelling tools are used for modelling different views sequentially proposed of the same problem. These views cover all the aspects that are involved in the system; based on process definitions for identifying responsible and defining the involved agents to propose the deployment in a distributed architecture that is both feasible and appropriate.

Ideological systems and its validation: a neutrosophic approach

Ideologies face two critical problems in the reality, the problem of commitment and the problem of validation. Commitment and validation are two separate phenomena, in spite of the near universal myth that the human is committed because his beliefs are valid. Ideologies not only seem external and valid but also worth whatever discomforts believing entails. In this paper the authors develop a theory of social commitment and social validation using concepts of validation of neutrosophic logic.

A multi-scaled approach for simulating chemical reaction systems

In this paper we give an overview of some very recent work, as well as presenting a new approach, on the stochastic simulation of multi-scaled systems involving chemical reactions. In many biological systems (such as genetic regulation and cellular dynamics) there is a mix between small numbers of key regulatory proteins, and medium and large numbers of molecules. In addition, it is important to be able to follow the trajectories of individual molecules by taking proper account of the randomness inherent in such a system. We describe different types of simulation techniques (including the stochastic simulation algorithm, Poisson Runge–Kutta methods and the balanced Euler method) for treating simulations in the three different reaction regimes: slow, medium and fast. We then review some recent techniques on the treatment of coupled slow and fast reactions for stochastic chemical kinetics and present a new approach which couples the three regimes mentioned above. We then apply this approach to a biologically inspired problem involving the expression and activity of LacZ and LacY proteins in E. coli, and conclude with a discussion on the significance of this work.

Exploiting uncertainty in nonlinear stochastic control problem

This work introduces a novel inversion-based neurocontroller for solving control problems involving uncertain nonlinear systems which could also compensate for multi-valued systems. The approach uses recent developments in neural networks, especially in the context of modelling statistical distributions, which are applied to forward and inverse plant models. Provided that certain conditions are met, an estimate of the intrinsic uncertainty for the outputs of neural networks can be obtained using the statistical properties of networks. More generally, multicomponent distributions can be modelled by the mixture density network. Based on importance sampling from these distributions a novel robust inverse control approach is obtained. This importance sampling provides a structured and principled approach to constrain the complexity of the search space for the ideal control law. The developed methodology circumvents the dynamic programming problem by using the predicted neural network uncertainty to localise the possible control solutions to consider. Convergence of the output error for the proposed control method is verified by using a Lyapunov function. Several simulation examples are provided to demonstrate the efficiency of the developed control method. The manner in which such a method is extended to nonlinear multi-variable systems with different delays between the input-output pairs is considered and demonstrated through simulation examples.

Agent Based Models of Competition and Collaboration

Swarm intelligence is a popular paradigm for algorithm design. Frequently drawing inspiration from natural systems, it assigns simple rules to a set of agents with the aim that, through local interactions, they collectively solve some global problem. Current variants of a popular swarm based optimization algorithm, particle swarm optimization (PSO), are investigated with a focus on premature convergence. A novel variant, dispersive PSO, is proposed to address this problem and is shown to lead to increased robustness and performance compared to current PSO algorithms. A nature inspired decentralised multi-agent algorithm is proposed to solve a constrained problem of distributed task allocation. Agents must collect and process the mail batches, without global knowledge of their environment or communication between agents. New rules for specialisation are proposed and are shown to exhibit improved eciency and exibility compared to existing ones. These new rules are compared with a market based approach to agent control. The eciency (average number of tasks performed), the exibility (ability to react to changes in the environment), and the sensitivity to load (ability to cope with differing demands) are investigated in both static and dynamic environments. A hybrid algorithm combining both approaches, is shown to exhibit improved eciency and robustness. Evolutionary algorithms are employed, both to optimize parameters and to allow the various rules to evolve and compete. We also observe extinction and speciation. In order to interpret algorithm performance we analyse the causes of eciency loss, derive theoretical upper bounds for the eciency, as well as a complete theoretical description of a non-trivial case, and compare these with the experimental results. Motivated by this work we introduce agent "memory" (the possibility for agents to develop preferences for certain cities) and show that not only does it lead to emergent cooperation between agents, but also to a signicant increase in efficiency.