For many years, the progress in agent-oriented development has focused on tools and methods for particular development phases. This has not been enough for the industry to accept agent technology as we expected. Our hypothesis is that the Agent-Oriented Software Engineering (AOSE) community has not recognized the kind of development methods that industry actually demands. We propose to analyze this hypothesis starting with a more precise definition of what an AOSE methodology should be. This definition is the first step for a review of the current progress of an illustrative selection of methodologies, looking for missing elements and future lines of improvement. The result is an account of how well the AOSE community is meeting the software lifecycle needs. It can be advanced that AOSE methodologies are far from providing all the answers industry requires and that effort has grounded mainly in requirements, design, and implementation phases.

With the significant advances in the area of autonomous agents and multi-agent systems in the last decade, promising technologies for the development and engineering of multi-agent systems have emerged. The result is a variety of agent-oriented programming languages, development frameworks, execution platforms, and tools that facilitate building and engineering of multi-agent systems. This paper provides an overview of the multi-agent programming research field and explains the aim and characteristics of various multi-agent programming languages and development frameworks. This overview is complemented with a discussion on the current trends and challenges in this research community.

Self-organizing software systems are an increasingly attractive approach to highly distributed, decentralized, dynamic applications. In some domains (such as the Internet), the interaction of originally independent systems yields a self-organizing system de facto, and engineers must take these characteristics into account to manage them. This review surveys current work in this field and outlines its main themes, identifies challenges for future research, and addresses the continuity between software engineering in general and techniques appropriate for self-organizing systems.

Coordination infrastructures play a central role in the engineering of multiagent systems. Since the advent of agent technology, research on coordination infrastructures has produced a significant number of infrastructures with varying features. In this paper, we review the the state-of-the-art coordination infrastructures with the purpose of identifying open research challenges that next generation coordination infrastructures should address. Our analysis concludes that next generation coordination infrastructures must address a number of challenges: (i) to become socially aware, by facilitating human interaction within a MAS; (ii) to assist agents in their decision making by providing decision support that helps them reduce the scope of reasoning and facilitates the achievement of their goals; and (iii) to increase openness to support on-line, fully decentralised design and execution. Furthermore, we identify some promising approaches in the literature, together with the research issues worth investigating, to cope with such challenges.