995 resultados para Multiagent system
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Optimizing collective behavior in multiagent systems requires algorithms to find not only appropriate individual behaviors but also a suitable composition of agents within a team. Over the last two decades, evolutionary methods have emerged as a promising approach for the design of agents and their compositions into teams. The choice of a crossover operator that facilitates the evolution of optimal team composition is recognized to be crucial, but so far, it has never been thoroughly quantified. Here, we highlight the limitations of two different crossover operators that exchange entire agents between teams: restricted agent swapping (RAS) that exchanges only corresponding agents between teams and free agent swapping (FAS) that allows an arbitrary exchange of agents. Our results show that RAS suffers from premature convergence, whereas FAS entails insufficient convergence. Consequently, in both cases, the exploration and exploitation aspects of the evolutionary algorithm are not well balanced resulting in the evolution of suboptimal team compositions. To overcome this problem, we propose combining the two methods. Our approach first applies FAS to explore the search space and then RAS to exploit it. This mixed approach is a much more efficient strategy for the evolution of team compositions compared to either strategy on its own. Our results suggest that such a mixed agent-swapping algorithm should always be preferred whenever the optimal composition of individuals in a multiagent system is unknown.
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Organisations in Multi-Agent Systems (MAS) have proven to be successful in regulating agent societies. Nevertheless, changes in agents' behaviour or in the dynamics of the environment may lead to a poor fulfilment of the system's purposes, and so the entire organisation needs to be adapted. In this paper we focus on endowing the organisation with adaptation capabilities, instead of expecting agents to be capable of adapting the organisation by themselves. We regard this organisational adaptation as an assisting service provided by what we call the Assistance Layer. Our generic Two Level Assisted MAS Architecture (2-LAMA) incorporates such a layer. We empirically evaluate this approach by means of an agent-based simulator we have developed for the P2P sharing network domain. This simulator implements 2-LAMA architecture and supports the comparison between different adaptation methods, as well as, with the standard BitTorrent protocol. In particular, we present two alternatives to perform norm adaptation and one method to adapt agents'relationships. The results show improved performance and demonstrate that the cost of introducing an additional layer in charge of the system's adaptation is lower than its benefits.
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La principal contribución de esta Tesis es la propuesta de un modelo de agente BDI graduado (g-BDI) que permita especificar una arquitetura de agente capaz de representar y razonar con actitudes mentales graduadas. Consideramos que una arquitectura BDI más exible permitirá desarrollar agentes que alcancen mejor performance en entornos inciertos y dinámicos, al servicio de otros agentes (humanos o no) que puedan tener un conjunto de motivaciones graduadas. En el modelo g-BDI, las actitudes graduadas del agente tienen una representación explícita y adecuada. Los grados en las creencias representan la medida en que el agente cree que una fórmula es verdadera, en los deseos positivos o negativos permiten al agente establecer respectivamente, diferentes niveles de preferencias o de rechazo. Las graduaciones en las intenciones también dan una medida de preferencia pero en este caso, modelan el costo/beneficio que le trae al agente alcanzar una meta. Luego, a partir de la representación e interacción de estas actitudes graduadas, pueden ser modelados agentes que muestren diferentes tipos de comportamiento. La formalización del modelo g-BDI está basada en los sistemas multi-contextos. Diferentes lógicas modales multivaluadas se han propuesto para representar y razonar sobre las creencias, deseos e intenciones, presentando en cada caso una axiomática completa y consistente. Para tratar con la semántica operacional del modelo de agente, primero se definió un calculus para la ejecución de sistemas multi-contextos, denominado Multi-context calculus. Luego, mediante este calculus se le ha dado al modelo g-BDI semántica computacional. Por otra parte, se ha presentado una metodología para la ingeniería de agentes g-BDI en un escenario multiagente. El objeto de esta propuesta es guiar el diseño de sistemas multiagentes, a partir de un problema del mundo real. Por medio del desarrollo de un sistema recomendador en turismo como caso de estudio, donde el agente recomendador tiene una arquitectura g-BDI, se ha mostrado que este modelo es valioso para diseñar e implementar agentes concretos. Finalmente, usando este caso de estudio se ha realizado una experimentación sobre la flexibilidad y performance del modelo de agente g-BDI, demostrando que es útil para desarrollar agentes que manifiesten conductas diversas. También se ha mostrado que los resultados obtenidos con estos agentes recomendadores modelizados con actitudes graduadas, son mejores que aquellos alcanzados por los agentes con actitudes no-graduadas.
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BDI agent languages provide a useful abstraction for complex systems comprised of interactive autonomous entities, but they have been used mostly in the context of single agents with a static plan library of behaviours invoked reactively. These languages provide a theoretically sound basis for agent design but are very limited in providing direct support for autonomy and societal cooperation needed for large scale systems. Some techniques for autonomy and cooperation have been explored in the past in ad hoc implementations, but not incorporated in any agent language. In order to address these shortcomings we extend the well known AgentSpeak(L) BDI agent language to include behaviour generation through planning, declarative goals and motivated goal adoption. We also develop a language-specific multiagent cooperation scheme and, to address potential problems arising from autonomy in a multiagent system, we extend our agents with a mechanism for norm processing leveraging existing theoretical work. These extensions allow for greater autonomy in the resulting systems, enabling them to synthesise new behaviours at runtime and to cooperate in non-scripted patterns.
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Of the ways in which agent behaviour can be regulated in a multiagent system, electronic contracting – based on explicit representation of different parties' responsibilities, and the agreement of all parties to them – has significant potential for modern industrial applications. Based on this assumption, the CONTRACT project aims to develop and apply electronic contracting and contract-based monitoring and verification techniques in real world applications. This paper presents results from the initial phase of the project, which focused on requirements solicitation and analysis. Specifically, we survey four use cases from diverse industrial applications, examine how they can benefit from an agent-based electronic contracting infrastructure and outline the technical requirements that would be placed on such an infrastructure. We present the designed CONTRACT architecture and describe how it may fulfil these requirements. In addition to motivating our work on the contract-based infrastructure, the paper aims to provide a much needed community resource in terms of use case themselves and to provide a clear commercial context for the development of work on contract-based system.
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This thesis proposes an architecture of a new multiagent system framework for hybridization of metaheuristics inspired on the general Particle Swarm Optimization framework (PSO). The main contribution is to propose an effective approach to solve hard combinatory optimization problems. The choice of PSO as inspiration was given because it is inherently multiagent, allowing explore the features of multiagent systems, such as learning and cooperation techniques. In the proposed architecture, particles are autonomous agents with memory and methods for learning and making decisions, using search strategies to move in the solution space. The concepts of position and velocity originally defined in PSO are redefined for this approach. The proposed architecture was applied to the Traveling Salesman Problem and to the Quadratic Assignment Problem, and computational experiments were performed for testing its effectiveness. The experimental results were promising, with satisfactory performance, whereas the potential of the proposed architecture has not been fully explored. For further researches, the proposed approach will be also applied to multiobjective combinatorial optimization problems, which are closer to real-world problems. In the context of applied research, we intend to work with both students at the undergraduate level and a technical level in the implementation of the proposed architecture in real-world problems
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The use of intelligent agents in multi-classifier systems appeared in order to making the centralized decision process of a multi-classifier system into a distributed, flexible and incremental one. Based on this, the NeurAge (Neural Agents) system (Abreu et al 2004) was proposed. This system has a superior performance to some combination-centered methods (Abreu, Canuto, and Santana 2005). The negotiation is important to the multiagent system performance, but most of negotiations are defined informaly. A way to formalize the negotiation process is using an ontology. In the context of classification tasks, the ontology provides an approach to formalize the concepts and rules that manage the relations between these concepts. This work aims at using ontologies to make a formal description of the negotiation methods of a multi-agent system for classification tasks, more specifically the NeurAge system. Through ontologies, we intend to make the NeurAge system more formal and open, allowing that new agents can be part of such system during the negotiation. In this sense, the NeurAge System will be studied on the basis of its functioning and reaching, mainly, the negotiation methods used by the same ones. After that, some negotiation ontologies found in literature will be studied, and then those that were chosen for this work will be adapted to the negotiation methods used in the NeurAge.
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Society, as we know it today, is completely dependent on computer networks, Internet and distributed systems, which place at our disposal the necessary services to perform our daily tasks. Moreover, and unconsciously, all services and distributed systems require network management systems. These systems allow us to, in general, maintain, manage, configure, scale, adapt, modify, edit, protect or improve 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 don’t consider network management systems during the development stage of main distributed systems, then there could be serious consequences or even total failures in the development of the distributed systems. It is necessary, therefore, to consider the management of the systems within the design of distributed systems and systematize their conception to minimize the impact of the management of networks within the project of distributed systems. In this paper, we present a formalization method of the conceptual modelling for design of a network management system through the use of formal modelling tools, thus allowing from the definition of processes to identify those responsible for these. Finally we will propose a use case to design a conceptual model intrusion detection system in network.
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As emoções são consideradas a regra central de nossas vidas, tendo grande impacto na tomada de decisões, ações, memória, atenção, etc. Sendo assim, existe grande interesse em simulá-las em ambientes computacionais, possibilitando que situações do cotidiano humano possam ser estudadas em ambientes controlados. Embora existam modelos teóricos para o funcionamento de emoções, estes por si só são insuficientes para uma simulação precisa em meios computacionais. Tendo como base um destes modelos, o modelo OCC, essa dissertação propõe a simulação de emoções em ambientes mutiagentes através da criação de uma rede Bayesiana capaz de traduzir estímulos gerados neste ambiente em emoções. A utilização de redes Bayesianas combinadas à estrutura do modelo OCC busca a adição de imprevisibilidade ao modelo, além de fornecê-lo uma estrutura computacional. A aplicação do modelo proposto a um sistema multiagentes proporciona o estudo da influência das emoções sobre as ações e comportamento dos agentes, possibilitando um estudo de comparação entre os resultados obtidos ao se realizar uma simulação multiagentes clássica e uma simulação multiagentes contendo emoções. De forma a validar e avaliar seu funcionamento, é apresentado o estudo da aplicação da rede Bayesiana de emoções sobre um modelo multiagentes exemplo, observando as variações que as emoções provocam sobre o comportamento dos agentes.
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Este trabalho propõe o desenvolvimento de um modelo de suporte á comunicação entre agentes e uma Ontologia com informações imprecisas. Os conceitos desta ontologia podem possuir sinônimos possibilitando a interpretação de termos linguísticos imprecisos. Tal problema é relacionado às questões de desenvolvimento da comunicação em Sistemas Multiagentes, possuindo como referência uma base de conhecimento da qual estes agentes possam requisitar informações. Neste estudo, a premissa do modelo é o de ser útil como componente na utilização por desenvolvedores que queiram utilizar de forma simplificada uma conexão com uma Ontologia para dar suporte na comunicação. Para o presente estudo são discutidos os conceitos sobre a comunicação no ambiente multiagentes. Também é realizada uma revisão sobre o desenvolvimento de Ontologias, de forma a criar uma ontologia para os agentes. A lógica nebulosa, baseado em variáveis linguísticas, servirá como modeladora da imprecisão da informação, dando suporte a essa questão com a Ontologia e a comunicação. De forma a validar o modelo proposto, é realizado um estudo de caso no sistema multiagentes das hortas urbanas do Parque San Jerónimo, de Sevilha, Espanha.
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El presente trabajo consiste en la elaboración de un sistema multiagente capaz de realizar simulaciones de enfermedades epidémicas, en determinados entornos, que pueden ser creados por los usuarios del sistema, así como la población que los ocupa, donde cada humano es un agente Jade. El trabajo se compone a su vez de cuatro módulos principales: una aplicación web realizada JSF, una aplicación de escritorio implementada en Java, el propio sistema multiagente que realiza las simulaciones, desarrollado usando Java sobre el framework de Jade y un servidor web que contiene al sistema multiagente y a la aplicación web mencionados anteriormente.El sistema desarrollado permite una gran cantidad de configuraciones sobre todos los aspectos que pueden influir en la simulación de una epidemia, como por ejemplo, parámetros de los entornos (tamaño, nivel de desarrollo, población de riesgo, etc.), población (porcentaje de población activa, estudiante, etc.) y enfermedades, así como sobre la propia simulación, ajustando por ejemplo el número de días de la duración o la probabilidad de que una persona decida ir a trabajar si está enferma. Además de realizar simulaciones, el sistema permite almacenarlas y consultarlas posteriormente, pudiendo tanto reproducirlas de nuevo como consultar información estadística detallada sobre la misma, así como distintas gráficas que muestran la evolución de la epidemia a lo largo de la simulación.Para garantizar un funcionamiento óptimo del sistema, este se ha ajustado y probado mediante diversas pruebas de estrés que garantizan que el rendimiento del mismo durante la realización de simulaciones es adecuado. Todo esto conforma un sistema cuya finalidad es la obtención de datos que puedan ser útiles de cara al estudio de enfermedades infecciosas potencialmente epidémicas y permitan extraer conclusiones sobre las mismas, ayudando al mejor entendimiento de este tipo de enfermedades y su comportamiento en determinados entornos.
Resumo:
El presente trabajo consiste en elaborar un sistema que permita simular epidemias en un entorno a través de agentes que representan a los habitantes del entorno simulado. El trabajo consta de cuatro partes: una aplicación web realizada en JSF, una aplicación de escritorio realizado en Java, un sistema multiagente, que se encarga de realizar la simulación, realizado en Java junto al framework JADE y un servidor web que contiene la aplicación web y el sistema multiagente. La simulación, el entorno y la enfermedad pueden ser configuradas, por parte del usuario, con distintos parámetros necesarios para la realización de la simulación. Una vez realizada la simulación, ésta puede ser visualizada a través de una animación y/o a través de un gráfico que representa la evolución de la simulación. Con el fin de que el sistema tuviera un funcionamiento óptimo, se han desarrollado pruebas de estrés aumentando el número de días y de personas para poder comprobar la solidez del sistema y así realizar mejoras si es necesario. Todo esto conforma un sistema cuya finalidad es obtener unos datos a partir de los cuales se pueden realizar distintos estudios y sacar conclusiones a partir de ellos, ayudando a investigar cómo se comporta una epidemia en unas determinadas condiciones y también distintas formas de poder combatirlas
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Este trabajo de fin de grado tiene como objetivo realizar un sistema multiagente para simular el desarrollo de las enfermedades epidemiológicas en un entorno concreto. Para ello se plantea hacer un servidor que haga una simulación, especificándole diversos parámetros del entorno, de la enfermedad y otros propios de la simulación. Estos parámetros se pueden especificar desde una aplicación web y desde una aplicación de escritorio. También se podrá visualizar esta simulación desde las dos aplicaciones, una vez que la simulación haya finalizado. Se decide estructurar el sistema de esta forma para dejar la mayor parte del cómputo en manos del servidor. El software se desarrolla íntegramente en Java, haciendo así que sea multiplataforma. Para el desarrollo de este proyecto se ha investigado sobre la programación orientada a agentes y sobre los distintos modelos de epidemias existentes. Este es un proyecto grupal, formado por dos compañeros y yo. Ha sido un arduo trabajo de análisis, diseño, implementación y prueba del software por parte de todos. Para facilitar todo este proceso, la sincronización y el reparto de tareas se sigue una metodología de desarrollo ágil.
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Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores
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Supervising and controlling the many processes involved in petroleum production is both dangerous and complex. Herein, we propose a multiagent supervisory and control system for handle continuous processes like those in chemical and petroleum industries In its architeture, there are agents responsible for managing data production and analysis, and also the production equipments. Fuzzy controllers were used as control agents. The application of a fuzzy control system to managing an off-shore installation for petroleum production onto a submarine separation process is described. © 2008 IEEE.