This article proposes an agent-oriented methodology called MAS-CommonKADS and develops a case study. This methodology extends the knowledge engineering methodology CommonKADS with techniquesfrom objectoriented and protocol engineering methodologies. The methodology consists of the development of seven models: Agent Model, that describes the characteristics of each agent; Task Model, that describes the tasks that the agents carry out; Expertise Model, that describes the knowledge needed by the agents to achieve their goals; Organisation Model, that describes the structural relationships between agents (software agents and/or human agents); Coordination Model, that describes the dynamic relationships between software agents; Communication Model, that describes the dynamic relationships between human agents and their respective personal assistant software agents; and Design Model, that refines the previous models and determines the most suitable agent architecture for each agent, and the requirements of the agent network.

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.

The architecture of a multi-agent system can naturally be viewed as an organised society of individuals (i.e., as a computational organisation). For this reason, we believe organisational abstractions should play a central role in the analysis and design of such systems. To this end, the concepts of agent roles and role models are increasingly being used to specify and design multi-agent systems. However, this is not the full picture. In t...

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.

Agent technologies are now being applied to the development of large-scale commercial and industrial software systems. Such systems are complex, involving hundreds, perhaps thousands of agents, and there is a pressing need for system modelling techniques that permit their complexity to be effectively managed, and principled methodologies to guide the process of system design. Without adequate techniques to support the design process, such systems will not be sufficiently reliable, maintainable or extensible, will be difficult to comprehend, and their elements will not be re-usable. In this paper

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Abstract. Tropos is a novel agent-oriented software development methodology founded on two key features: (i) the notions of agent, goal, plan and various other knowledge level concepts are fundamental primitives used uniformly throughout the software development process; and (ii) a crucial role is assigned to requirements analysis and specification when the system-to-be is analyzed with respect to its intended environment. This paper provides a (first) detailed account of the Tropos methodology. In particular, we describe the basic concepts on which Tropos is founded and the types of models one builds out of them. We also specify the analysis process through which design flows from external to system actors through a goal analysis and delegation. In addition, we provide an abstract syntax for Tropos diagrams and other linguistic constructs. 1

Multi-agent systems... In this paper we introduce three additional organisational concepts - organisational rules, organisational structures, and organisational patterns - and discuss why we believe they are necessary for the complete specification of computational organisations. In particular, we focus on the concept of organisational rules and introduce a formalism, based on temporal logic, to specify them. This formalism is then used to drive the definition of the organisational structure and the identification of the organisational patterns. Finally, the paper sketches some guidelines for a methodology for agent-oriented systems based on our expanded set of organisational abstractions.

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.

Agent-based computing is a promising approach for developing applications in complex domains. However, despite the great deal of research in the area, a number of challenges still need to be faced (i) to make agent-based computing a widely accepted paradigm in software engineering practice, and (ii) to turn agent-oriented software abstractions into practical tools for facing the complexity of modern application areas. In this paper, after a short introduction to the key concepts of agent-based computing (as they pertain to software engineering), we characterise the emerging key issues in multiagent systems (MASs) engineering. In particular, we show that such issues can be analysed in terms of three different ‘‘scales of observation’’, i.e., in analogy with the scales of observation of physical phenomena, in terms of micro, macro, and meso scales. Based on this characterisation, we discuss, for each scale of observation, what are the peculiar engineering issues arising, the key research challenges to be solved, and the most promising research directions to be explored in the future.