The application of agent technology to real applications needs the development of a methodology which supports all the Software Development Life Cycle (SDLC) of an agent based system including its management. This paper proposes an extension of CommonKADS for fitting the characteristics of the agent approach into the SDLC and the definition of a new model, the coordination model, for describing the coordination protocols. 1 The need for a methodology In spite of the great interest in the agent technology in the scientific community, and the introduction of terms such as Agent-Based Software Engineering (Wooldridge & Fisher, 1994) and Multi-Agent Systems engineering (Muller, 1992), there has been little work in defining a methodology for designing agents and agent based systems as mentioned in (Jennings, 1995; Jennings & Wooldridge, 1995; Muller, 1992). A first approach for the definition of a general methodology for multiagent systems (MAS) is here presented, which has been developed ...

This paper proposes an approach for the development of multi-agent architectures based on a conceptual model set which is implementation independent. We propose an extension of the CommonKADS methodology to multi-agent systems; run-time aspects are taken into consideration, in particular, the structuring of problem-solving knowledge at a conceptual level guarantees flexibility and modularity and an execution level. The construction of agent models is a compositional process based on the CommonKADS-close conceptual models resulting from five analysis steps. Inference structures have appeared to be a useful means to guide the implementation of our competence-encapsulating agent model. In fact, we use them to identify procedures from a program library during implementation.

Knowledge acquisition is a well known bottleneck activity in the development of knowledge-based systems. The model-driven approach to knowledge acquisition is to use a library of generic problem solving methods, where each one is specialized for a certain kind of application task, such as diagnosis or product configuration, that guides knowledge acquisition in that kind of application. The thesis describes three case-studies of using the model-driven approach to knowledge acquisition, in particular within the CommonKADS methodology, and contributions motivated by the results of those case-studies. An important difficulty in model-driven knowledge acquisition is that a generic problem solving method often has to be adapted to the features of the current application. A widely accepted proposal for dealing with this difficulty, and others, is to organize libraries as hierarchical collections of task decomposition methods, rather than as collections of complete problem solving methods. Although such libraries reduce the need for adaptations, the case-studies show that adaptation is still a major difficulty. Two complementary approaches for further reducing the difficulties of adaptation are pursued. To support adaptation, general guidelines are provided for the process of adapting a selected generic problem solving method to the features of the current application. The guidelines are tested in two of the case-studies. To prevent unnecessary adaptations, general principles for task decomposition methods are proposed, which can be used to identify weaknesses that might cause unnecessary adaptations in applications. The principles are evaluated by showing that most of the modifications that were necessary in one of the case-studies could have been prevented by applying thes...

This document is part of a research project partially funded by the ESPRIT Programme of the Commission of the European Communities as project number 5248. The partners in this project are Gap Gemini Innovation (F), Cap Gemini Programator (S), Netherlands Energy Research Foundation ECN (NL), ENTEL SA (ESP), IBM France (F), Lloyd's Register (UK), Swedisch Institute of Computer Science (S), Siemens AG (D), Touche Ross MC (UK), University of Amsterdam (NL) and Free University of Brussels (B)

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