This paper presents a methodology for agent-oriented analysis and design. The methodology is general, in that it is applicable to a wide range of multi-agent systems, and comprehensive, in that it deals with both the macro-level (societal) and the micro-level (agent) aspects of systems. The methodology is founded on the view of a system as a computational organisation consisting of various interacting roles. We illustrate the methodology through a case study (an agent-based business process management system).

Gaining wide acceptance for the use of agents in industry requires both relating it to the nearestantecU3O1 teccU3O1 (objec t-oriented software development) and usingartifac2 to support the development environment throughout the full systemlifec34I1 We address both of these requirements in this paper by desc51U"3 some of the mostcstU2 requirements for modeling agents and agent-based systems---using a set of UML idioms and extensions. This paper illustrates theapproac by presenting a three-layer AUML representation for agent interacOU" protocO andcdUO6521 byinc14O4U other useful agent-based extensions to UML.

. This article introduces the current agent-oriented methodologies. It discusseswhat approacheshave been followed (mainly extending existing objectoriented and knowledge engineering methodologies), the suitability of these approaches for agent modelling, and some conclusions drawn from the survey. 1 Introduction Agent technology has received a great deal of attention in the last few years and, as a result, the industry is beginning to get interested in using this technology to develop its own products. In spite of the different developed agent theories, languages, architectures and the successful agent-based applications, very little work for specifying (and applying) techniques to develop applications using agent technology has been done. The role of agent-oriented methodologies is to assist in all the phases of the life cycle of an agent-based application, including its management. This article reviews the current approaches to the development of an agent-oriented (AO) methodology. ...

Abstract. Software engineers continually strive to develop tools and techniques to manage the complexity that is inherent in software systems. In this article, we argue that intelligent agents and multi-agent systems are just such tools. We begin by reviewing what is meant by the term “agent”, and contrast agents with objects. We then go on to examine a number of prototype techniques proposed for engineering agent systems, including methodologies for agent-oriented analysis and design, formal specification and verification methods for agent systems, and techniques for implementing agent specifications. 1

This paper describes the Multiagent Systems Engineering (MaSE) methodology. MaSE is a general purpose, methodology for developing heterogeneous multiagent systems. MaSE uses a number of graphically based models to describe system goals, behaviors, agent types, and agent communication interfaces. MaSE also provides a way to specify architecture-independent detailed definition of the internal agent design. An example of applying the MaSE methodology is also presented.

Gaining wide acceptance for the use of agents in industry requires both relating it to the nearest antecedent technology (objectoriented software development) and using artifacts to support the development environment throughout the full system lifecycle. We address both of these requirements using AUML, the Agent UML (Unified Modeling Language)—a set of UML idioms and extensions. This paper illustrates the approach by presenting a three-layer AUML representation for agent interaction protocols: templates and packages to represent the protocol as a whole; sequence and collaboration diagrams to capture inter-agent dynamics; and activity diagrams and state charts to capture both intra-agent and inter-agent dynamics.

The metaphors of autonomous agents and agent societies havethepotential to make a signi cant impact on the processes of analysis, design, and development of complex software systems on the Internet. In this chapter, we concentrate predominantly on agent societies, and show howwork on coordination models and technologies provides apowerful framework for the engineering of Internet-based, multi-agent systems. First, we introduce the concepts of agent, multi-agent system, and agent-oriented software engineering, and highlight the speci c issues that arise when we take the Internet as the environment thatagents inhabit. We thenprovide a brief survey of the state of the art in the area of agent-oriented methodologies, paying particular attention to the Gaia methodology for agent-oriented analysis and design. Gaia was originally conceived for benevolent agents inhabiting closed systems. However, to broaden its scope, we show how insights from the area of coordination models can be incorporated in order to make it more suitable for developing Internet-based applications.

This paper presents the MESSAGE/UML agent oriented software engineering methodology and illustrates it on an analysis case study. The methodology covers MAS analysis and design and is intended for use in mainstream software engineering departments. MESSAGE extends UML by contributing agent knowledge level concepts, and diagrams with notations for viewing them. The diagrams extend UML class and activity diagrams. Categories and Subject Descriptors D.2.1 [Software Engineering]: Requirements/Specifications -- methodologies. General Terms Languages, Documentation. Keywords Agent, Methodology, UML, Analysis. 1.

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Abstract. An increasing number of methodologies and modelling methods are being proposed in the area of agent-oriented software engineering. However, one of the open problems in order for agent-oriented software engineering to become a “mainstream ” is a lack of consensus between the different analysis and design methods that have been proposed. Thus, this study proposes a framework to carry out an analysis or evaluation of the agent-oriented analysis and design modelling methods. The proposal, takes into consideration qualitative evaluation criteria employing quantitative methods. In order to clarify the proposal, this framework is also applied to a case study, and some interesting aspects are analysed from both a qualitative and a quantitative perspective.