The concept of an agent has become important in both artificial intelligence (AT) and mainstream computer science. Our aim in this paper is to point the reader at what we perceive to be the most important theoretical and practical issues associated with the design and construction of intelligent agents. For convenience, we divide these issues into three areas (though as the reader will see, the divisions are at times somewhat arbitrary). Agent theory is concerned with the question of what an agent is, and the use of mathematical formalisms for representing and reasoning about the properties of agents. Agent architectures can be thought of as software engineering models of agents; researchers in this area are primarily concerned with the problem of designing software or hardware systems that will satisfy the properties specified by agent theorists. Finally, agent languages are software systems for programming and experimenting with agents; these languages may embody principles proposed by theorists. The paper is not intended to serve as a tutorial introduction to all the issues mentioned; we hope instead simply to identify the most important issues, and point to work that elaborates on them. The article includes a short review of current and potential applications of agent technology.

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Systems composed of interacting autonomous agents offer a promising software engineering approach for developing applications in complex domains. However, this multiagent system paradigm introduces a number of new abstractions and design/development issues when compared with more traditional approaches to software development. Accordingly, new analysis and design methodologies, as well as new tools, are needed to effectively engineer such systems. Against this background, the contribution of this article is twofold. First, we synthesize and clarify the key abstractions of agent-based computing as they pertain to agent-oriented software engineering. In particular, we argue that a multiagent system can naturally be viewed and architected as a computational organization , and we identify the appropriate organizational abstractions that are central to the analysis and design of such systems. Second, we detail and extend the Gaia methodology for the analysis and design of multiagent systems. Gaia exploits the aforementioned organizational abstractions to provide clear guidelines for the analysis and design of complex and open software systems. Two representative case studies are introduced to exemplify Gaia's concepts and to show its use and effectiveness in different types of multiagent system.

Cooperative game theory is a branch of (micro-)economics that studies the behavior of self-interested agents in strategic settings where binding agreements among agents are possible. Our aim in this book is to present a survey of work on the computational aspects of cooperative game theory. We begin by formally defining transferable utility games in characteristic function form, and introducing key solution concepts such as the core and the Shapley value. We then discuss two major issues that arise when considering such games from a computational perspective: identifying compact representations for games, and the closely related problem of efficiently computing solution concepts for games. We survey several formalisms for cooperative games that have been proposed in the literature, including, for example, cooperative games defined on networks, as well as general compact representation schemes such as MC-nets and skill games. As a detailed case study, we consider weighted voting games: a widely-us...