2,275 research outputs found

    Topologies of agents interactions in knowledge intensive multi-agentsystems for networked information services

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    Agents in a multi-agent system (mAS) could interact and cooperate in many different ways. The topology of agent interaction determines how the agents control and communicate with each other, what are the control and communication capabilities of each agent and the whole system, and how efficient the control and communications are. In consequence, the topology affects the agents’ ability to share knowledge, integrate knowledge, and make efficient use of knowledge in MAS. This paper presents an overview of four major MAS topologic models, assesses their advantages and disadvantages in terms of agent autonomy, adaptation, scalability, and efficiency of cooperation. Some insights into the applicability for each of the topologies to different environment and domain specific applications are explored. A design example of the topological models to an information service management application is attempted to illustrate the practical merits of each topology

    A Review of Platforms for the Development of Agent Systems

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    Agent-based computing is an active field of research with the goal of building autonomous software of hardware entities. This task is often facilitated by the use of dedicated, specialized frameworks. For almost thirty years, many such agent platforms have been developed. Meanwhile, some of them have been abandoned, others continue their development and new platforms are released. This paper presents a up-to-date review of the existing agent platforms and also a historical perspective of this domain. It aims to serve as a reference point for people interested in developing agent systems. This work details the main characteristics of the included agent platforms, together with links to specific projects where they have been used. It distinguishes between the active platforms and those no longer under development or with unclear status. It also classifies the agent platforms as general purpose ones, free or commercial, and specialized ones, which can be used for particular types of applications.Comment: 40 pages, 2 figures, 9 tables, 83 reference

    Organization based multiagent architecture for distributed environments

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    [EN]Distributed environments represent a complex field in which applied solutions should be flexible and include significant adaptation capabilities. These environments are related to problems where multiple users and devices may interact, and where simple and local solutions could possibly generate good results, but may not be effective with regards to use and interaction. There are many techniques that can be employed to face this kind of problems, from CORBA to multi-agent systems, passing by web-services and SOA, among others. All those methodologies have their advantages and disadvantages that are properly analyzed in this documents, to finally explain the new architecture presented as a solution for distributed environment problems. The new architecture for solving complex solutions in distributed environments presented here is called OBaMADE: Organization Based Multiagent Architecture for Distributed Environments. It is a multiagent architecture based on the organizations of agents paradigm, where the agents in the architecture are structured into organizations to improve their organizational capabilities. The reasoning power of the architecture is based on the Case-Based Reasoning methology, being implemented in a internal organization that uses agents to create services to solve the external request made by the users. The OBaMADE architecture has been successfully applied to two different case studies where its prediction capabilities have been properly checked. Those case studies have showed optimistic results and, being complex systems, have demonstrated the abstraction and generalizations capabilities of the architecture. Nevertheless OBaMADE is intended to be able to solve much other kind of problems in distributed environments scenarios. It should be applied to other varieties of situations and to other knowledge fields to fully develop its potencial.[ES]Los entornos distribuidos representan un campo de conocimiento complejo en el que las soluciones a aplicar deben ser flexibles y deben contar con gran capacidad de adaptación. Este tipo de entornos está normalmente relacionado con problemas donde varios usuarios y dispositivos entran en juego. Para solucionar dichos problemas, pueden utilizarse sistemas locales que, aunque ofrezcan buenos resultados en términos de calidad de los mismos, no son tan efectivos en cuanto a la interacción y posibilidades de uso. Existen múltiples técnicas que pueden ser empleadas para resolver este tipo de problemas, desde CORBA a sistemas multiagente, pasando por servicios web y SOA, entre otros. Todas estas mitologías tienen sus ventajas e inconvenientes, que se analizan en este documento, para explicar, finalmente, la nueva arquitectura presentada como una solución para los problemas generados en entornos distribuidos. La nueva arquitectura aquí se llama OBaMADE, que es el acrónimo del inglés Organization Based Multiagent Architecture for Distributed Environments (Arquitectura Multiagente Basada en Organizaciones para Entornos Distribuidos). Se trata de una arquitectura multiagente basasa en el paradigma de las organizaciones de agente, donde los agentes que forman parte de la arquitectura se estructuran en organizaciones para mejorar sus capacidades organizativas. La capacidad de razonamiento de la arquitectura está basada en la metodología de razonamiento basado en casos, que se ha implementado en una de las organizaciones internas de la arquitectura por medio de agentes que crean servicios que responden a las solicitudes externas de los usuarios. La arquitectura OBaMADE se ha aplicado de forma exitosa a dos casos de estudio diferentes, en los que se han demostrado sus capacidades predictivas. Aplicando OBaMADE a estos casos de estudio se han obtenido resultados esperanzadores y, al ser sistemas complejos, se han demostrado las capacidades tanto de abstracción como de generalización de la arquitectura presentada. Sin embargo, esta arquitectura está diseñada para poder ser aplicada a más tipo de problemas de entornos distribuidos. Debe ser aplicada a más variadas situaciones y a otros campos de conocimiento para desarrollar completamente el potencial de esta arquitectura

    Calendar.help: Designing a Workflow-Based Scheduling Agent with Humans in the Loop

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    Although information workers may complain about meetings, they are an essential part of their work life. Consequently, busy people spend a significant amount of time scheduling meetings. We present Calendar.help, a system that provides fast, efficient scheduling through structured workflows. Users interact with the system via email, delegating their scheduling needs to the system as if it were a human personal assistant. Common scheduling scenarios are broken down using well-defined workflows and completed as a series of microtasks that are automated when possible and executed by a human otherwise. Unusual scenarios fall back to a trained human assistant who executes them as unstructured macrotasks. We describe the iterative approach we used to develop Calendar.help, and share the lessons learned from scheduling thousands of meetings during a year of real-world deployments. Our findings provide insight into how complex information tasks can be broken down into repeatable components that can be executed efficiently to improve productivity.Comment: 10 page
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