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.

Agent-oriented techniques represent an exciting new means of analysing, designing and building complex software systems. They have the potential to significantly improve current practice in software engineering and to extend the range of applications that can feasibly be tackled. Yet, to date, there have been few serious attempts to cast agent systems as a software engineering paradigm. This paper seeks to rectify this omission. Specifically, it will be argued that: (i) the conceptual apparatus of agent-oriented systems is well-suited to building software solutions for complex systems and (ii) agent-oriented approaches represent a genuine advance over the current state of the art for engineering complex systems. Following on from this view, the major issues raised by adopting an agent-oriented approach to software engineering are highlighted and discussed. 1.

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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

In a multi-agent environment, where self-motivated agents try to pursue their own goals, cooperation cannot be taken for granted. Cooperation must be planned for and achieved through communication and negotiation. We present a logical model of the mental states of the agents based on a representation of their beliefs, desires, intentions, and goals. We present argumentation as an iterative process emerging from exchanges among agents to persuade each other and bring about a change in intentions. We look at argumentation as a mechanism for achieving cooperation and agreements. Using categories identified from human multi-agent negotiation, we demonstrate how the logic can be used to specify argument formulation and evaluation. We also illustrate how the developed logic can be used to describe different types of agents. Furthermore, we present a general Automated Negotiation Agent which we implemented, based on the logical model. Using this system, a user can analyze and explore differe...

Software and knowledge... In this article, we argue that intelligent agents and agent-based systems offer novel opportunities for developing effective tools and techniques. Following a discussion on the classic subject of what makes software complex, we introduce intelligent agents as software structures capable of making "rational decisions". Such rational decision-makers are well-suited to the construction of certain types of software, which mainstream software engineering has had little success with. We then go on to examine a number of prototype techniques proposed for engineering agent systems, including formal specification and verification methods for agent systems, and techniques for implementing agent specifications

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

Multi-Agent Systems are increasingly complex, and the problem of their verification and validation is acquiring increasing importance. In this paper we show how a well known and effective verification technique, symbolic model checking, can be generalized to deal with Multi-Agent Systems. Our approach is fully amenable to the reuse of data structures used in symbolic model checking, Binary Decision Diagrams in particular, to deal with extremely large state spaces. A preliminary implementation of the approach in the NuMAS system shows promising results.

This paper introduces AgentSpeak(F), a variation of the BDI logic programming language AgentSpeak(L) intended to permit the model-theoretic verification of multi-agent systems. After briefly introducing AgentSpeak(F) and discussing its relationship to AgentSpeak(L), we show how AgentSpeak(F) programs can be transformed into Promela, the model specification language for the Spin model-checking system. We also describe how specifications written in a simplified form of BDI logic can be transformed into Spin-format linear temporal logic formul. With our approach, it is thus possible to automatically verify whether or not multi-agent systems implemented in AgentSpeak(F) satisfy specifications expressed as BDI logic formul. We illustrate our approach with a short case study, in which we show how BDI properties of a simulated auction system implemented in AgentSpeak(F) were verified.

A traditional approach for planning is to evaluate goal statements over state trajectories modeling predicted behaviors of an agent. This paper describes a powerful extension of this approach for handling complex goals for reactive agents. We describe goals by using a modal temporal logic that can express quite complex time, safety, and liveness constraints. Our method is based on an incremental planner algorithm that generates a reactive plan by computing a sequence of partially satisfactory reactive plans converging to a completely satisfactory one. Partial satisfaction means that an agent controlled by the plan accomplishes its goal only for some environment events. Complete satisfaction means that the agent accomplishes its goal whatever environment events occur during the execution of the plan. As such, our planner can be stopped at any time to yield a useful plan. An implemented prototype is used to evaluate our planner on empirical problems. Keywords: Planning, control, reactiv...