The concept of an agent has become important in both Artificial Intelligence (AI) 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 prop-erties 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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to stimulate the next wave of research on organization learning. It provides a conceptual framework for research on the differences and similarities of learning by individuals, groups, and organizations.

This paper provides an overview of research and development activities in the field of autonomous agents and multi-agent systems. It aims to identify key concepts and applications, and to indicate how they relate to one-another. Some historical context to the field of agent-based computing is given, and contemporary research directions are presented. Finally, a range of open issues and future challenges are highlighted.

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One reason why Distributed AI (DAI) technology has been deployed in relatively few real-size applications is that it lacks a clear and implementable model of cooperative problem solving which specifies how agents should operate and interact in complex, dynamic and unpredictable environments. As a consequence of the experience gained whilst building a number of DAI systems for industrial applications, a new principled model of cooperation has been developed. This model, called Joint Responsibility, has the notion of joint intentions at its core. It specifies pre-conditions which must be attained before collaboration can commence and prescribes how individuals should behave both when joint activity is progressing satisfactorily and also when it runs into difficulty. The theoretical model has been used to guide the implementation of a general-purpose cooperation framework and the qualitative and quantitative benefits of this implementation have been assessed through a series of comparativ...

The concept of an agent has recently become important in Artificial Intelligence (AI), and its relatively youthful subfield, Distributed AI (DAI). 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 the area into three themes (though as the reader will see, these 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 constructing 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 typically 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 key issues, and point to work that elaborates on them. The paper closes with a detailed bibliography, and some bibliographical remarks. 1

This paper considers the semantics of the agent communication language KQML. By using this language for communication, agents will be able to request and provide services. Indeed, numerous projects have shown how the language can profitably support interoperation among distributed agents. However, before becoming a widely-accepted standard, it would be worthwhile to examine the language in detail, especially the semantical issues it raises. This paper identifies numerous difficulties with the language, and an attempt is made to point to their resolution. The paper illustrates the kind of semantics we believe to be necessary to characterize agent communication languages, identifies an important adequacy condition "compositionality" and shows how to compose a question from a request and an inform. Finally, the paper discusses possible impacts to be felt on various KQML decisions from the semantical issues raised here.

The goal of this ongoing project is to develop an open agent architecture and accompanying user interface for networked desktop and handheld machines. The system we are building should support distributed execution of a user's requests, interoperabilityofmultiple application subsystems, addition of new agents, and incorporation of existing applications. It should also be transparent; users should not need to know where their requests are being executed, nor how. Finally, in order to facilitate the user's delegating tasks to agents, the architecture will be served byamultimodal interface, including pen, voice, and direct manipulation. Design considerations taken to support this functionality will be discussed below. INTRODUCTION Agents are all the rage. #Visioneering" videos, suchas Apple Computer's Knowledge Navigator, have helped to popularize the notion that programs endowed with agency, if not intelligence, are just around the corner. Soon, users need not themselves...

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