This chapter introduces the ADELFE methodology, an agent-oriented methodology dedicated to the design of systems that are complex, open, and not well-specified. The need for its development is justified by the theoretical background given in the first section, which also gives an overview of the concepts on which multi-agent systems developed with ADELFE are based. A methodology is composed of a process, a notation, and tools. Tools are presented in the second section and the process in the third one, using an information system case study to better visualize how to apply this process.
This paper is the synthesis of joint work realised in a technical forum group within the AgentLink III NoE framework, which elaborated on issues concerning self-organization and emergence in multi-agent systems (MAS). The work concluded on a common definition of the concepts of self-organization and emergence in MAS and the associated properties and characteristics. Also it developed towards an approach for selecting self-organization mechanisms using a number of selected reference case studies and a set of evaluation criteria.
Abstract. Several agent-oriented methodologies have been proposed over the last few years. Unlike the object-oriented domain and unfortunately for designers, most of the time, each methodology has its own purposes and few standardization works have been done yet, limiting the impact of agent design on the industrial world. By studying three existing methodologies -ADELFE, Gaia and PASSI -and the concepts related to them, this paper tries to find a means to unify their metamodels. Comparing a certain number of features at the agent or system level (such as the agent structure, its society or organization, its interactions capacities or how agents may be implemented) has enabled us to draw up a first version of a unified meta-model proposed as a first step toward interoperability between agent-oriented methodologies.
A challenge for our days is to provide new efficient CASE (Computer Aided Software Engineering) tools enabling MAS designers towards Model Driven Engineering (MDE) approaches. The goal of MDE is to improve the de-velopment process and the quality of the software produced. Our work focuses on two different aspects of MAS. The functional one, which is application de-pendent and close to the decision process of agents, and the operational one related to elementary capabilities of agents. For each point of view, we have de-fined specific meta-models. Our goal in this paper is to provide a mapping from the functional meta-model to the operational that constitutes a specific platform model. As we are interested in adaptive systems, we have to deal with adaptation both at the agent and the system level. We address this problem by respectively using the JavAct flexible architecture and the Adaptive MAS principles.
Complexity of near future and even nowadays applications is exponentially increasing. In order to tackle the design of such complex systems, being able to engineer self-organising systems is a promising approach. This way, the whole system will autonomously changes its behaviour as its parts locally reorganise themselves, always providing an adapted function. This paper proposes to focus on engineering such systems generating emergent functionalities. We will first define two important concepts to take into account in such a context: Emergence and Self-Organisation. Building on these two concepts, we will highlight three main challenges researchers have to cope with: (i) how to control the system at the macro level by only focusing on the design of agents at the micro level, (ii) what kind of tools, models and guides are needed to develop such systems in order to help designers and (iii) how validation of such systems can be achieved? Each of these three challenges will be explained and positioned in regard to the main existing approaches. Our solutions combining emergence and self-organisation will be expounded for each challenge.
OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. This is an author-deposited version published in : http://oatao.univ-toulouse.fr/ Eprints ID : 18173 Abstract-Mission planning for a constellation of Earth observation satellites is a complex problem raising significant technological challenges for tomorrow's space systems. The large numbers of customers requests and their dynamic introduction in the planning system result in a huge combinatorial search space with a potentially highly dynamical evolution requirements. The techniques used nowadays have several limitations, in particular, it is impossible to dynamically adapt the plan during its construction even for small modifications. Satellites of a constellation are planned in a chronological way instead of a more collective planning which can provide additional load balancing.In this paper, we propose to solve this difficult and highly dynamic problem using adaptive multi-agent systems, taking advantage from their self-adaptation and self-organization mechanisms. In the proposed system, the agents, through their local interactions, allow to dynamically reach a good solution, while ensuring a controlled distribution of tasks within the constellation of satellites. Finally, a comparison with a classical chronological greedy algorithm, commonly used in the spatial domain, highlights the advantages of the presented system.
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