Ontological Engineering and Mapping in Multiagent Systems Development

Multiagent systems have received much attention in recent years due to their advantages in complex, distributed environments. Previous work at the Air Force Institute of Technology has developed a methodology for analyzing, designing, and developing multiagent systems, called Multiagent Systems Engineering (MaSE). MaSE currently does not address the information domain of the system, which is an integral part of designing proper system execution. This research extends the MaSE methodology to include the use of ontologies for information domain specification. The extensions allow the designer to specify information flow by using objects from the ontology as parameters in agent conversations. The developer can then ensure system functionality by verifying that each agent has the information required to accomplish the system goals. To fully describe the system design, the developer must describe the relationships between the system ontology and any agent component ontologies. This research also developed a ranking model to assist the user with creating such mappings, to show the relationships between the objects in the ontologies

Designing and specifying mobility within the multiagent systems engineering methodology

Recently, researchers have created many platforms and applications for mobile agents; however, current Agent-Oriented Software Engineering (AOSE) methodologies have yet not fully integrated the unique properties of these mobile agents. This paper attempts to bridge the gap between current AOSE methodologies and mobile agent systems by incorporating mobility into the established Multiagent Systems Engineering (MaSE) methodology. We accomplished this by adding a move command to the MaSE analysis models and then defined the required transformations to incorporate the required functionality into the design. Finally, we translated the design models into Java-based agents that operate within a mobile agent environment. 1

Visual Execution Analysis for Multiagent Systems

Multiagent systems have become increasingly important in developing complex software systems. Multiagent systems introduce collective intelligence and provide benefits such as flexibility, scalability, decentralization, and increased reliability. A software agent is a high-level software abstraction that is capable of performing given tasks in an environment without human intervention. Although multiagent systems provide a convenient and powerful way to organize complex software systems, developing such system is very complicated. To help manage this complexity this research develops a methodology and technique for analyzing, monitoring and troubleshooting multiagent systems execution. This is accomplished by visualizing a multiagent system at multiple levels of abstraction to capture the relationships and dependencies among the agents

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

Comparing Agent Software Development Methodologies Using the Waterfall Model

This paper explores three widely published agent-based software development methodologies, Multiagent Systems Engineering Methodology (MaSE), Prometheus, and Tropos, using the traditional Waterfall model of software engineering as a baseline. Differences between the methodologies are examined and gaps between the agent-based methodologies and the Waterfall approach are identified

A multi-agent system for administering the prescription of anti-retroviral and anti-TB drugs

Thesis (M. Tech.) -- Central University of Technology, Free State, 2007Multi-agent systems (MAS) consist of a number of autonomous agents that communicate among themselves to coordinate their activities in order to solve collectively a complex problem that cannot be tackled by any agent individually. These kinds of systems are appropriate in many domains where problems that are complex, distributed and heterogeneous require communication and coordination between separate autonomous agents, which may be running on different machines distributed over the Internet and are located in many different places. In the health care domain, MAS have been used for distributed patient scheduling, organ and tissue transplant management, community care, decision support, training and so on. One other promising area of application is in the prescription of antiretroviral and antiTB drugs. The drugs used to treat the two diseases have many and similar side effects that complicate the prescription process. These factors have to be considered when prescribing medication to a person coinfected with HIV and tuberculosis. This is usually done manually using drug recommendation tables, which are complicated to use and require a great deal of decisionmaking. The design and implementation of a multiagent system that assists health care staff in carrying out the complex task of combining antiretroviral and antiTB drugs in an efficient way is described. The system consists of a number of collaborating agents requiring the communication of complex and diverse forms of information between a variety of clinical and other settings, as well as the coordination between groups of health care professionals (doctors, nurses, counsellors, etcetera.) with very different skills and roles. The agents in the system include: patient agents, nurse agents, lab agents, medication agents and physician agents. The agents may be hosted on different machines, located in many different places distributed over the Internet. The system saves time, minimises decision errors and increases the standard of health care provided to patients

Development of a Graphical Tool to integrate the Prometheus AEOlus methodology and Jason Platform

Software Engineering (SE) is an area that intends to build high-quality software in a systematic way. However, traditional software engineering techniques and methods do not support the demand for developing Multiagent Systems (MAS). Therefore a new subarea has been studied, called Agent Oriented Software Engineering (AOSE). The AOSE area proposes solutions to specific issues related to the development of agent oriented systems. There are several methodologies to model MAS, however, until now, there is not a standard modelling language because they are very complex systems, and involve several different concepts. Another issue of this subarea is that there are very few tools that are able to automatically generate code, reducing its acceptance in the software development market. In this work, we propose a tool to support the Prometheus AEOlus Methodology, because it provides modelling artifacts to all MAS dimensions proposed by ~Demazeau: agents, environment, interactions and organization. The tool supports all Prometheus AEOlus artifacts and it can automatically generated code to the agent and interaction dimensions in the AgentSpeak(L) language, which is the language used in the Jason platform. We have done some validations with the proposed tool and a case study is presented. Our results indicate that our tool has full compatibility with the Jason platform, and it is able to automatic generate code in AgentSpeak(L). As future work, we intend to develop the integration of the artifacts with the JaCaMo framework, enabling a full integration between our tool and the Prometheus AEOlus methodology

Modelagem de Objetos Inteligentes de Aprendizagem utilizando a metodologia MaSE

O presente trabalho apresenta a modelagem de um Sistema Multiagente para Objetos Inteligentes de Aprendizagem utilizando a metodologia para Engenharia de Sistemas Multiagentes, denominada MaSE (Multiagent System Engineering). Estametodologia permite descrever desde uma especificação inicial do sistema até a sua implementação através da interligação entre seus diagramas

Estudo de um metodologia orientada a agentes: um protótipo para um ambiente virtual

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Engenharia de Produção.Pesquisa que aborda o estudo de uma metodologia orientada a agentes e a utilização de uma ferramenta para a especificação de sistemas orientados a agentes tendo como base a especificação de agentes de interface. Neste trabalho são analisadas metodologias para a modelagem de sistemas baseados em agente, onde a Metodologia MaSE (Multiagent System Engineering) demonstrou ser a mais indicada para a modelagem de um sistema colaborativo, dirigindo o analista por todas as fases de análise e projeto de sistemas MultiAgentes. Foi utilizado o Framework agentTool, que é uma ferramenta que dá suporte a metodologia MaSE, através de um ambiente acionado por menus e diagramas manipuláveis graficamente em janelas. A utilização do Agenttool como ferramenta para projetar e modelar agentes demonstrou-se eficaz, permitindo ao projetista passar rapidamente da fase de análise para a fase de implementação