Analysis and design of multiagent systems using MAS-CommonKADS

This article proposes an agent-oriented methodology called MAS-CommonKADS and develops a case study. This methodology extends the knowledge engineering methodology CommonKADSwith techniquesfrom objectoriented and protocol engineering methodologies. The methodology consists of the development of seven models: Agent Model, that describes the characteristics of each agent; Task Model, that describes the tasks that the agents carry out; Expertise Model, that describes the knowledge needed by the agents to achieve their goals; Organisation Model, that describes the structural relationships between agents (software agents and/or human agents); Coordination Model, that describes the dynamic relationships between software agents; Communication Model, that describes the dynamic relationships between human agents and their respective personal assistant software agents; and Design Model, that refines the previous models and determines the most suitable agent architecture for each agent, and the requirements of the agent network

Automated highway systems : platoons of vehicles viewed as a multiagent system

Tableau d'honneur de la Faculté des études supérieures et postdoctorales, 2005-2006La conduite collaborative est un domaine lié aux systèmes de transport intelligents, qui utilise les communications pour guider de façon autonome des véhicules coopératifs sur une autoroute automatisée. Depuis les dernières années, différentes architectures de véhicules automatisés ont été proposées, mais la plupart d’entre elles n’ont pas, ou presque pas, attaqué le problème de communication inter véhicules. À l’intérieur de ce mémoire, nous nous attaquons au problème de la conduite collaborative en utilisant un peloton de voitures conduites par des agents logiciels plus ou moins autonomes, interagissant dans un même environnement multi-agents: une autoroute automatisée. Pour ce faire, nous proposons une architecture hiérarchique d’agents conducteurs de voitures, se basant sur trois couches (couche de guidance, couche de management et couche de contrôle du trafic). Cette architecture peut être utilisée pour développer un peloton centralisé, où un agent conducteur de tête coordonne les autres avec des règles strictes, et un peloton décentralisé, où le peloton est vu comme une équipe d’agents conducteurs ayant le même niveau d’autonomie et essayant de maintenir le peloton stable.Collaborative driving is a growing domain of Intelligent Transportation Systems (ITS) that makes use of communications to autonomously guide cooperative vehicles on an Automated Highway System (AHS). For the past decade, different architectures of automated vehicles have been proposed, but most of them did not or barely addressed the inter-vehicle communication problem. In this thesis, we address the collaborative driving problem by using a platoon of cars driven by more or less autonomous software agents interacting in a Multiagent System (MAS) environment: the automated highway. To achieve this, we propose a hierarchical driving agent architecture based on three layers (guidance layer, management layer and traffic control layer). This architecture can be used to develop centralized platoons, where the driving agent of the head vehicle coordinates other driving agents by applying strict rules, and decentralized platoons, where the platoon is considered as a team of driving agents with a similar degree of autonomy, trying to maintain a stable platoon

Cooperative production networks - multiagent modeling and planning

Consumer goods are mainly produced in multiple steps through a long process. These steps are often done by separate, independent production nodes (enterprises), linked by supply chains. The networks of enterprises — where members have their own objectives and act in an autonomous, rational way to reach their goals — can be naturally modeled by agent-based methodology. The inner structure of each enterprise is similar in the sense that it contains separated planning functions (e.g., production-, inventory-, capacity planning). While the operation inside an enterprise can be controlled centrally, the interaction between the nodes could be synchronized only by negotiation and coordination. Coordination can be based on protocols which regulate information, material and financial flows alike. In this paper we expose an agent-based organizational model of production networks and suggest some planning algorithms which can handle the uncertainty of demand. In addition, we outline the first results of our ongoing research, an analysis of the asymmetric information case and an appropriate coordination mechanism

Wireless Sensor Networks And Data Fusion For Structural Health Monitoring Of Aircraft

This thesis discusses an architecture and design of a sensor web to be used for structural health monitoring of an aircraft. Also presented are several prototypes of critical parts of the sensor web. The proposed sensor web will utilize sensor nodes situated throughout the structure. These nodes and one or more workstations will support agents that communicate and collaborate to monitor the health of the structure. Agents can be any internal or external autonomous entity that has direct access to affect a given system. For the purposes of this document, an agent will be defined as an autonomous software resource that has the ability to make decisions for itself based on given tasks and abilities while also collaborating with others to find a feasible answer to a given problem regarding the structural health monitoring system. Once the agents have received relevant data from nodes, they will utilize applications that perform data fusion techniques to classify events and further improve the functionality of the system for more accurate future classifications. Agents will also pass alerts up a self-configuring hierarchy of monitor agents and make them available for review by personnel. This thesis makes use of previous results from applying the Gaia methodology for analysis and design of the multiagent system

Wireless Sensor Networks And Data Fusion For Structural Health Monitoring Of Aircraft

This thesis discusses an architecture and design of a sensor web to be used for structural health monitoring of an aircraft. Also presented are several prototypes of critical parts of the sensor web. The proposed sensor web will utilize sensor nodes situated throughout the structure. These nodes and one or more workstations will support agents that communicate and collaborate to monitor the health of the structure. Agents can be any internal or external autonomous entity that has direct access to affect a given system. For the purposes of this document, an agent will be defined as an autonomous software resource that has the ability to make decisions for itself based on given tasks and abilities while also collaborating with others to find a feasible answer to a given problem regarding the structural health monitoring system. Once the agents have received relevant data from nodes, they will utilize applications that perform data fusion techniques to classify events and further improve the functionality of the system for more accurate future classifications. Agents will also pass alerts up a self-configuring hierarchy of monitor agents and make them available for review by personnel. This thesis makes use of previous results from applying the Gaia methodology for analysis and design of the multiagent system

Multiagent Systems Engineering: A Methodology for Analysis and Design of Multiagent Systems

This thesis defines a methodology for the creation of multiagent systems, the Multiagent Systems Engineering (MaSE) methodology. The methodology is a key issue in the development of any complex system and there is currently no standard or widely used methodology in the realm of multiagent systems. MaSE covers the entire software lifecycle, starting from an initial prose specification, and creating a set of formal design documents in a graphical style based on a formal syntax. The final product of MaSE is a diagram describing the deployment of a system of intelligent agents that communicate through structured conversations. MaSE was created with the mention of being supported by an automated design tool. The tool built to support MaSE, agent Tool, is a multiagent system development tool for designing and synthesizing complex multiagent systems

The Visual Social Distancing Problem

One of the main and most effective measures to contain the recent viral outbreak is the maintenance of the so-called Social Distancing (SD). To comply with this constraint, workplaces, public institutions, transports and schools will likely adopt restrictions over the minimum inter-personal distance between people. Given this actual scenario, it is crucial to massively measure the compliance to such physical constraint in our life, in order to figure out the reasons of the possible breaks of such distance limitations, and understand if this implies a possible threat given the scene context. All of this, complying with privacy policies and making the measurement acceptable. To this end, we introduce the Visual Social Distancing (VSD) problem, defined as the automatic estimation of the inter-personal distance from an image, and the characterization of the related people aggregations. VSD is pivotal for a non-invasive analysis to whether people comply with the SD restriction, and to provide statistics about the level of safety of specific areas whenever this constraint is violated. We then discuss how VSD relates with previous literature in Social Signal Processing and indicate which existing Computer Vision methods can be used to manage such problem. We conclude with future challenges related to the effectiveness of VSD systems, ethical implications and future application scenarios.Comment: 9 pages, 5 figures. All the authors equally contributed to this manuscript and they are listed by alphabetical order. Under submissio

Machine Learning And A Workflow Engine For An Agent-Based Structural Health Monitoring System

This thesis reports on work in machine learning and high-performance computing for structural heath monitoring. The data used are acoustic emission signals, and we classify these signals according to source mechanisms, those associated with crack growth being particularly significant. The work reported here is part of a larger project to develop an agent-based structural health monitoring system. The agents are proxies for communication- and computation-intensive techniques and respond to the situation at hand by determining an appropriate constellation of techniques. The techniques thus structured are executed by a workflow engine, which is part of the contribution reported here. It is critical that the system have a repertoire of classifiers with different characteristics so that a combination appropriate for the situation at hand can generally be found. The classifiers are trained using machine-learning techniques, and we report on investigations we conducted on three supervised and two unsupervised learning techniques to determine which techniques are the best to use in a particular situation

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