Adding debugging support to the Prometheus methodology

This paper describes a debugger which uses the design artifacts of the Prometheus agent-oriented software engineering methodology to alert the developer testing the system, that a specification has been violated. Detailed information is provided regarding the error which can help the developer in locating its source. Interaction protocols specified during design, are converted to executable Petri net representations. The system can then be monitored at run time to identify situations which do not conform to specified protocols. A process for monitoring aspects of plan selection is also described. The paper then describes the Prometheus Design Tool, developed to support the Prometheus methodology, and presents a vision of an integrated development environment providing full life cycle support for the development of agent systems. The initial part of the paper provides a detailed summary of the Prometheus methodology and the artifacts on which the debugger is based

Software Language Engineering: Interaction and Usability Modeling of Language Editors

Background: Domain-Specific Languages (DSLs) are programming languages created to a specific domain that a user has pre-conceived. Multi-Agent Systems (MAS) represent a set of systems interacting within an environment, in which many intelligent agents interact with each other. Usability is a property of something that is "capable of being used"and "convenient and practicable for use". Barišic et al. introduced a conceptual framework that supports the iterative development process of DSLs concerning the usability evaluation. Semantic Web Enabled Agent Modeling Language (SEA_ML) is a DSL that supports the modeling and generation of action-based systems for MAS and the Semantic Web. It is defined by 44 visual notations. Objective: Improve SEA_ML’s usability using "The "Physics"of Notations" principles to create a new visual notation for SEA_ML. Method: (1) Participants test the current notation and the new notation on four exercises. For each exercise, a SUS questionnaire is presented. Participants should have better results on the exercises with the new notation. (2) Participants select the notations for SEA_ML. Participants receive a list with figures including the current and the new notation, alongside a set of descriptions for each of the semantic constructs of SEA_ML. Participants should select more icons from the new notation. Results: With the results gathered from each experience it is not clear that the new visual notations are better than the current notations. Limitation: The results from the guidelines were not evaluated broadly. Conclusion: The results for each experiment are not clear that the new notation is better than the current notation. This thesis is part of a scientific and technological co-operation between NOVA LINCS research center at Universidade Nova de Lisboa, Portugal, and Ege University International Computer Institute, Turkey. regarding the project Developing a Framework on Evaluating Domain specific Modeling Languages for Multi-Agent Systems

Towards Open Agent Systems Through Dynamic Incorporation

This work tackles the problem of providing a mechanism and infrastructure for allowing a given Multiagent System (MAS) to become open, allowing the incorporation of newly incoming agents to participate within the existing society. For this, a conceptual analysis of the so-called conciliation problem is presented, covering the diverse levels and issues involved in such a process. Our Dynamic Incorporation Architecture is presented, which implements an infrastructure for allowing the participation of external agents into a specific multiagent system by incorporating the appropriate behaviours upon arrival. Our multiagent architecture for dynamic incorporation covers three levels: semantics, communication and interaction and has been applyed in a book-trading e-market scenario

Can Agent Oriented Software Engineering Be Used to Build MASs Product Lines?

On the one hand, the Software Product Lines (SPL) field is devoted to build a core architecture for a family of products from which concrete products can be derived rapidly by means of reuse. On the other hand, Agent-Oriented Software Engineering (AOSE) is a software engineering paradigms dedicated to build software applications composed of organizations of agents. Bringing AOSE to the industrial world may prettily benefit from SPL advantages. Using SPL phi losophy, a company will be able to define a core MAS from which concrete prod ucts will be derived for each customer. This can reduce time-to-market, costs, etcetera. In this paper, we expose the similarities between AOSE and SPL con cluding the viability of future research in Multi-Agent Systems Product Lines (MAS-PL)

An Agent-Based Solution for the Berth Allocation Problem

This work presents the development of MABAP, a decision support system based on the agent technology that helps in solving the problem of berth allocation for ships within a port. The Berth Allocation Problem (BAP) regards the logistics involved in planning and controlling the berthing of vessels. A software architecture in terms of agents is presented; Berths and Ships representing the actors in the system, BerthRequest and BerthPlanner as representatives of ships and berths in the planning process, and finally the Dock and Central agents representing the dock or pier. The architecture modeling was done using PASSI methodology for the design of agent-oriented systems, and the implementation was done in JADE, a Javabased development environment for multiagent systems. To validate the resulting support system, tests were carried out in which the user can choose different portpolicy scenarios, ranging from maximizing vessels throughput to maximize berths use

Многоагентные технологии для индустриальных приложений: реальность и перспектива

Since early 1990th, multi-agent technology is evaluated as one of the most perspective design and implementation technologies for industrial scale distributed applications. However, the practice has falsified all the prognoses and expectations. The paper examines the current state-of-the-art in industrial use of the multi-agent technology. It analyzes external and internal reasons preventing broad practical use of the technology and formulates the lessons learnt through this examination. Finally, the paper outlines the basic issues to be revised in order to practically realize the great potential of the multi-agent technology. The paper also shows, by example, that multi-agent technology has currently no alternative for many novel most important applications including Internet of Things.Уже в течение более чем четверти века технология многоагентных систем рассматривается как одна из наиболее перспективных технологий концептуализации и программной реализации сложных распределенных систем. Однако в практике происходит совсем иное: индустрия практически не использует эту технологию, и это несмотря на то, что на практике появляются все новые и новые классы приложений, для которых эта технология представляется чуть ли ни единственно возможной технологией разработки. В статье анализируются недавние прогнозы и реальные достижения в части практического применения многоагентных систем на промышленном уровне. Выявляются проблемы, которые в настоящее время препятствуют широкому промышленному внедрению многоагентных систем и технологий, а также пути их преодоления. Анализируются классы приложений, в реализации которых многоагентные технологии имеют неоспоримые преимущества и оцениваются перспективы развития этих технологий до уровня индустриального применения

Collective and emergent problem solving based on multi-agent systems : principles and applications

A multi-agent system is composed of numerous entities, called agents, interacting in various ways between them and their common environment. This technology is applied in many domains like computer vision, robotics, system simulation or electronic commerce. We consider that problems occuring in signal processing could also be tackled by this technology. We present first the basic tools available for multi-agent systems designers : models, platforms and methodologies. Two projects illustrate our purpose : SCALA in the management of aerospace fighter patrol, and goods routing. We focus then on the adaptation ability of these systems considered as an emergent problem solving question. We detailed in this field the AMAS (Adaptive Multi-Agent System) theory allowing a MAS design where the global fonction is derived from the cooperative self-organisation of its components. An example on flood forecast gives implementation information of this theory.Un système multi-agent est constitué d’un grand nombre d’entités, appelées agents, en interaction entre elles au sein d’un même environnement. Cette technologie aborde de nombreux domaines d’applications comme la vision par ordinateur, la robotique, la simulation de systèmes, le commerce électronique. Nous considérons que les questions abordées en traitement du signal sont très pertinentes dans un cadre multi-agent. Nous présentons d’abord les principaux outils dont disposent les concepteurs de systèmes multi-agents à savoir : des modèles, des plates-formes et des méthodes de développement. Puis, le projet SCALA de simulation de résolution de problèmes par des patrouilles aériennes et un projet de simulation de système de transports illustrent la résolution de problèmes à l’aide de systèmes multi-agents. Ensuite, nous nous intéressons plus particulièrement aux capacités d’adaptation de tels systèmes que nous abordons comme une question de résolution émergente de problèmes. Dans ce cadre nous décrivons en détail la théorie AMAS (Adaptive Multi-Agent System) qui permet de concevoir des systèmes dont la fonction globale émerge à partir d’un processus d’auto-organisation coopérative de ses parties. Une application en prévision de crues donne une indication plus précise des capacités de telles approches

Design methodology for ontology-based multi-agent applications (MOMA)

Software agents and multi-agent systems (MAS) have grown into a very active area of research and commercial development activity. There are many current emerging real-world applications spanning multitude of diverse domains. In the context of agents, ontology has been widely recognised for their significant benefits to interoperability, reusability, and both development and operational aspects of agent systems and applications. Ontology-based multi-agent systems (OBMAS) exploit these advantages in providing intelligent and semantically aware applications. In addressing the lack of support for ontology in existing methodologies for multi-agent development, this thesis proposes a design methodology for the building of such intelligent multi-agent applications called MOMA. This alternative approach focuses on the development of ontology as the driving force of the development process. By allowing the domain and characteristics of utilisation and experimentation to be dictated through ontology, researchers and domain experts can specify the agent application without any knowledge of agent design and lower level programming. Through the use of a structured ontology model and the use of integrated tools, this approach contributes towards the building of semantically aware intelligent applications for use by researchers and domain experts. MOMA is evaluated through case studies in two different domains: financial services and e-Health

Towards a comprehensive agent-oriented software engineering methodology

Recently, agent systems have proven to be a powerful new approach for designing and developing complex and distributed software systems. The agent area is one of the most dynamic and exciting areas in computer science today, because of the agents ability to impact the lives and work of all of us. Developing multi-agent systems for complex and distributed systems entails a robust methodology to assist developers to develop such systems in appropriate way. In the last ten years, many of agent oriented methodologies have been proposed. Although, these methodologies are based on strong basis they still suffer from a set of shortcomings and they still have the problems of traditional distributed systems as well as the difficulties that arise from flexibility requirements and sophisticated interactions. This thesis proposed a new agent oriented software engineering methodology called: Multi-Agent System Development (MASD) for development of multi-agent systems. The new methodology is provided by a set of guidelines, methods, models, and techniques that facilitate a systematic software development process. The thesis makes the following contributions: The main contribution of this thesis is to build a new methodology for the development of multi-agent systems. It is based upon the previous existing methodologies. It is aimed to develop a complete life-cycle methodology for designing and developing MASs. The new methodology is considered as an attempt to solve some of the problems that existing methodologies suffer from. The new methodology is established based on three fundamental aspects: concepts, models, and process. These three aspects are considered as a foundation for building a solid methodology. The concepts are all the necessary MAS concepts that should be available in order to build the models of the new methodology in a correct manner. The models include modeling techniques, modeling languages, a diagramming notation, and tools that can be used to analysis and design the agent system. The process is a set of steps or phases describe how the new methodology works in detail. The new methodology is built to bridge the gap between design models and existing agent implementation languages. It provides refined design models that can be directly implemented in an available programming language or use a dedicated agent-oriented programming language which provides constructs to implement the high-level design concepts such as Jadex, JADE, JACK, etc. The MASD methodology also uses an important concept called triggers and relies heavily on agent roles. The role concept is considered one of the most important aspects that represent agent behaviour. The trigger concept is also considered as an important aspect that represents agent reactivity. The new methodology captures the social agent aspects by utilizing well-known techniques such as use case maps, which enable developers to identify social aspects from the problem specification. MASD methodology is developed based on the essential software engineering issues such as preciseness, accessibility, expressiveness, domain applicability, modularity, refinement, model derivation, traceability, and clear definitions. The MASD methodology is provided by a plain and understandable development process through the methodology phases. It captures the holistic view of the system components, and commutative aspects, which should be recognized before designing the methodology models. This is achieved by using well-known techniques such as UCMs and UML UCDs. The resulting methodology was obtained by performing several steps. First, a review study “literature review” of different agent methodologies is carried out to capture their strengths and weaknesses. This review study started with the conceptual framework for MAS to discuss the common terms and concepts that are used in the thesis. The aim is to establish the characteristics of agent-oriented methodologies, and see how these characteristics are suited to develop multi-agent systems. Secondly, a requirement for a novel methodology is presented. These requirements are discussed in detail based on the three categories: concepts, models, and process. Thirdly, the new mature methodology is developed based on existing methodologies. The MASD methodology is composed of four phases: the system requirement phase, analysis phase, design phase and implementation phase. The new methodology covers the whole life cycle of agent system development, from requirement analysis, architecture design, and detailed design to implementation. Fourthly, the methodology is illustrated by a case study on an agent-based car rental system. Finally, a framework for evaluating agent-oriented methodologies is performed. Four methodologies including MASD are evaluated and compared by performing a feature analysis. This is carried out by evaluating the strengths and weaknesses of each participating methodology using a proposed evaluation framework called the Multi-agent System Analysis and Design Framework (MASADF). The evaluation framework addresses several major aspects of agent-oriented methodologies, such as: concepts, models and process