Organization based multiagent architecture for distributed environments

[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

Sistemas Tutores Inteligentes Multiagentes: los agentes docentes en el módulo tutor

Los STI basados en agentes (STM: Sistemas Tutores Multiagentes) requieren de la definición de características tales como la forma de comunicación y los criterios de sociabilidad. Si bien el paradigma de agentes proporciona ciertas ventajas tales como la gran tolerancia a fallas, existen aspectos que se deben definir y que son esenciales: la comunicación, la coordinación, la interacción y la sociabilidad. A partir de un esquema básico para la interacción del alumno con el docente, se estudian las diferentes opciones en cuanto a características de los agentes para llevar a cabo una sesión de aprendizaje de tipo “uno a uno”. Se propone un modelo de agente docente en el módulo tutor y se reconoce a la herramienta a utilizar para el diseño de este sistema en el campo de los agentes, a fin de continuar con la siguiente etapa en la investigación.The STI based on agents (MTS: Multiagent Tutorial Systems) require the definition of characteristics such as the kind of communication and sociability criteria. Although the paradigm of agents provides certain advantages like the great faults’s tolerance, exist some aspects that are due to define and that are essential: communication, coordination, interaction and sociability. From a basic scheme for interaction of students with teachers, different options as the agents characteristics to carry out a "one to one" session, are presented. A model of educational agent in the tutorial module is set out, and is recognized the tool to use for the design of this system in the agents ’s field, in order to continue the research.V Workshop de Tecnología Informática Aplicada en Educación (WTIAE)Red de Universidades con Carreras en Informática (RedUNCI

Diseño de Sistemas Tutores Inteligentes con Tecnología de Agentes: Los Agentes Docentes en el Módulo Tutor

A partir de un esquema básico, de interacción del alumno con los docentes, se estudian las diferentes características de los agentes para llevar a cabo una sesión de aprendizajes de tipo   “uno a uno”. Se propone un modelo de agente docente en el módulo tutor, y se reconoce a la herramienta a utilizar para el diseño de este sistema en el campo de los agentes, a fin de continuar con la siguiente etapa en la investigación. A partir de un esquema básico, de interacción del alumno con los docentes, se estudian las diferentes características de los agentes para llevar a cabo una sesión de aprendizajes de tipo “uno a uno”. Se propone un modelo de agente docente en el módulo tutor, y se reconoce a la herramienta a utilizar para el diseño de este sistema en el campo de los agentes, a fin de continuar con la siguiente etapa en la investigación

Sistemas Tutores Inteligentes Multiagentes: los agentes docentes en el módulo tutor

Los STI basados en agentes (STM: Sistemas Tutores Multiagentes) requieren de la definición de características tales como la forma de comunicación y los criterios de sociabilidad. Si bien el paradigma de agentes proporciona ciertas ventajas tales como la gran tolerancia a fallas, existen aspectos que se deben definir y que son esenciales: la comunicación, la coordinación, la interacción y la sociabilidad. A partir de un esquema básico para la interacción del alumno con el docente, se estudian las diferentes opciones en cuanto a características de los agentes para llevar a cabo una sesión de aprendizaje de tipo “uno a uno”. Se propone un modelo de agente docente en el módulo tutor y se reconoce a la herramienta a utilizar para el diseño de este sistema en el campo de los agentes, a fin de continuar con la siguiente etapa en la investigación.The STI based on agents (MTS: Multiagent Tutorial Systems) require the definition of characteristics such as the kind of communication and sociability criteria. Although the paradigm of agents provides certain advantages like the great faults’s tolerance, exist some aspects that are due to define and that are essential: communication, coordination, interaction and sociability. From a basic scheme for interaction of students with teachers, different options as the agents characteristics to carry out a "one to one" session, are presented. A model of educational agent in the tutorial module is set out, and is recognized the tool to use for the design of this system in the agents ’s field, in order to continue the research.V Workshop de Tecnología Informática Aplicada en Educación (WTIAE)Red de Universidades con Carreras en Informática (RedUNCI

A unified approach to the development and usage of mobile agents

Mobile agents are an interesting approach to the development of distributed systems. By moving freely accross the network, they allow for the distribution of computation as well as gathering and filtering of information in an autonomous way. Over the last decade, the agent research community has decidedly achieved tremendous results. However, the community was not able to provide easy to use toolkits to make this paradigm available to a broader audience. By embracing simplicity during the creation of a formal model and a reference implementation to create and execute instances of that model, our aim is to enable a wide audience – even non-experts – to create, adapt and use mobile agents. The proposed model allows for the creation of agents by combining atomic, self-contained building blocks and we provide an approachable, easy to use graphical editor for the creation of model instances. In two evaluations, we could reinforce our believes that, with the achieved results, we could reach our aims

Social Mental Shaping: Modelling the Impact of Sociality on Autonomous Agents' Mental States

This paper presents a framework that captures how the social nature of agents that are situated in a multi-agent environment impacts upon their individual mental states. Roles and relationships provide an abstraction upon which we develop the notion of social mental shaping. This allows us to extend the standard Belief-Desire-Intention model to account for how common social phenomena (e.g. cooperation, collaborative problem-solving and negotiation) can be integrated into a unified theoretical perspective that reflects a fully explicated model of the autonomous agent's mental state

Reputation for complex societies

Reputation, the germ of gossip, is addressed in this chapter as a distributed instrument for social order. In literature, reputation is shown to promote (a) social control in cooperative contexts—like social groups and subgroups—and (b) partner selection in competitive ones, like (e-) markets and industrial districts. Current technology that affects, employs and extends reputation, applied to electronic markets or multi-agent systems, is discussed in light of its theoretical background. In order to compare reputation systems with their original analogue, a social cognitive model of reputation is presented. The application of the model to the theoretical study of norm-abiding behaviour and partner selection are discussed, as well as the refinement and improvement of current reputation technology. The chapter concludes with remarks and ideas for future research.</p

Rational Coordination in Multi-Agent Environments

We adopt the decision-theoretic principle of expected utility maximization as a paradigm for designing autonomous rational agents, and present a framework that uses this paradigm to determine the choice of coordinated action. We endow an agent with a specialized representation that captures the agent's knowledge about the environment and about the other agents, including its knowledge about their states of knowledge, which can include what they know about the other agents, and so on. This reciprocity leads to a recursive nesting of models. Our framework puts forth a representation for the recursive models and, under the assumption that the nesting of models is finite, uses dynamic programming to solve this representation for the agent's rational choice of action. Using a decision-theoretic approach, our work addresses concerns of agent decision-making about coordinated action in unpredictable situations, without imposing upon agents pre-designed prescriptions, or protocols, about standard rules of interaction. We implemented our method in a number of domains and we show results of coordination among our automated agents, among human-controlled agents, and among our agents coordinating with human-controlled agents.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/44002/1/10458_2004_Article_272540.pd

Reputation

In this chapter, the role of reputation as a distributed instrument for social order is addressed. A short review of the state of the art will show the role of reputation in promoting (a) social control in cooperative contexts - like social groups and subgroups - and (b) partner selection in competitive contexts, like (e-) markets and industrial districts. In the initial section, current mechanisms of reputation - be they applied to electronic markets or MAS - will be shown to have poor theoretical backgrounds, missing almost completely the cognitive and social properties of the phenomenon under study. In the rest of the chapter a social cognitive model of reputation developed in the last decade by some of the authors will be presented. Its simulation-based applications to the theoretical study of norm-abiding behaviour, partner selection and to the refinement and improvement of current reputation mechanisms will be discussed. Final remarks and ideas for future research will conclude the chapte