This paper’s focus is on key issues related to the identification of appropriate abstractions for agent-based software engineering, and on the definition of a suitable methodology for the analysis and design of complex applications in terms of multiagent systems (MASs).

The work reported on in the paper is appropriate for the current state of this field; the paper describes the organizational abstractions that are necessary for agent-oriented software engineering. This differs from previous work in that it focuses on the particular organizational abstractions that are appropriate for the software engineering process, rather than on the specific technologies to implement them.

The authors argue that agent-oriented computing is an appropriate software engineering paradigm for the analysis, design, and development of many contemporary software systems. To demonstrate this, they provide a lengthy and detailed description of their key concepts for agent-based computing and multiagent systems development methodology. An extended literature review of related work is provided; the authors present many of the problems encountered in developing multiagent systems, and clearly state their extensions. Their concepts for the analysis and design of a multiagent system are documented in a methodology called the Gaia methodology. The authors illustrate their arguments by using, as examples, two real-world applications: a manufacturing system, and a conference management system.

Although a considerable part of this work addresses the key concepts of agent-based computing, as they pertain to agent-oriented software engineering, the paper itself is rather important, due to its development and provision of a methodology, centered around organizational abstractions, for the analysis and design of open multiagent systems. Potential applications of this could be the development of software applications for the management of open multiagent systems, such as electronic transactions via the Web. It is not easy, however, to identify or predict the potential results, which may be positive.

Finally, the authors claim that much work remains to be done on advancing the widespread acceptance of agent-based computing as a software engineering paradigm, and to this end, they make suggestions for future work.

This is a research study intended for researchers interested in developing multiagent systems. Although, in general, this is a well-written paper, I would expect, in such a lengthy work, to see some fragments of software implementations (code examples of applications), if only in an appendix. This would have helped readers to better understand the authors’ views on agent-oriented software engineering.

The level of novelty of this work, in relation to the extensive comparative literature review included, appears to be satisfactory. The credibility of this work--although it seems to be validated initially by the investigation of two real-world applications, and later on with a well-documented description of the Gaia methodology--could be extended further with more practical example cases.