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.

Trust is a judgement of unquestionable utility — as humans we use it every day of our lives. However, trust has suffered from an imperfect understanding, a plethora of definitions, and informal use in the literature and in everyday life. It is common to say “I trust you, ” but what does that mean? This thesis provides a clarification of trust. We present a formalism for trust which provides us with a tool for precise discussion. The formalism is implementable: it can be embedded in an artificial agent, enabling the agent to make trust-based decisions. Its applicability in the domain of Distributed Artificial Intelligence (DAI) is raised. The thesis presents a testbed populated by simple trusting agents which substantiates the utility of the formalism. The formalism provides a step in the direction of a proper understanding and definition of human trust. A contribution of the thesis is its detailed exploration of the possibilities of future work in the area. Summary 1. Overview This thesis presents an overview of trust as a social phenomenon and discusses it formally. It argues that trust is: • A means for understanding and adapting to the complexity of the environment. • A means of providing added robustness to independent agents. • A useful judgement in the light of experience of the behaviour of others. • Applicable to inanimate others. The thesis argues these points from the point of view of artificial agents. Trust in an artificial agent is a means of providing an additional tool for the consideration of other agents and the environment in which it exists. Moreover, a formalisation of trust enables the embedding of the concept into an artificial agent. This has been done, and is documented in the thesis. 2. Exposition There are places in the thesis where it is necessary to give a broad outline before going deeper. In consequence it may seem that the subject is not receiving a thorough treatment, or that too much is being discussed at one time! (This is particularly apparent in the first and second chapters.) To present a thorough understanding of trust, we have proceeded breadth first in the introductory chapters. Chapter 3 expands, depth first, presenting critical views of established researchers.

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 presents a high-level framework for analysing and designing intelligent agents. The framework's key abstraction mechanism is a new computer level called the Social Level. The Social Level sits immediately above the Knowledge Level, as defined by Allen Newell, and is concerned with the inherently social aspects of multiple agent systems. To illustrate the working of this framework, an important new class of agent is identified and then specified. Socially responsible agents retain their local autonomy but still draw from, and provide resources to, the larger community. Through empirical evaluation, it is shown that such agents produce both good system-wide performance and good individual performance. 1. INTRODUCTION The number of multi-agent systems being designed and built is rapidly increasing as software agents gain acceptance as a powerful and useful technology for solving complex problems (Chaib-draa, 1995; Jennings, 1994; PAAM, 1996). As applications become more comple...

THE aim of this thesis is to investigate logical formalisms for describing, reasoning about, specifying, and perhaps ultimately verifying the properties of systems composed of multiple intelligent computational agents. There are two obvious resources available for this task. The first is the (largely AI) tradition of reasoning about the intentional notions (belief, desire, etc.). The second is the (mainstream computer science) tradition of temporal logics for reasoning about reactive systems. Unfortunately, neither resource is ideally suited to the task: most intentional logics have little to say on the subject of agent architecture, and tend to assume that agents are perfect reasoners, whereas models of concurrent systems from mainstream computer science typically deal with the execution of individual program instructions. This thesis proposes a solution which draws upon both resources. It defines a model of agents and multi-agent systems, and then defines two execution models, which ...

Abstract. This paper presents the notion of multi-agent simulation that is based on the definition of computational agents that represent individual organisms (or groups of organisms) in a one to one correspondence. We discuss the properties of multi-agent simulation. We then present a multiagent simulation system based on the definition of reactive agents whose behavior is governed by the selection of simple competing tasks due to stimulus's perception. An example of a simulation of an ant colony follows as an illustration of the multiple domains in which multi-agent simulation may be used. 1.

Because we think that plans or strategies are useful for coordinating multiple agents, and because we hypothesize that most of the plans we use are build partly by us and partly by our immediate environment (which includes other agents), this paper is devoted to the conditions in which strategies can be viewed as the result of interactions between simple agents, each of them having only local information about the state of the world. Our approach is based on the study of some examples of reactive agents applications. Their features arebriefly described and we underline, in each of them, what we call the emergent strategies obtained from the local interactions between the agents. Three examples are studied this way: the eco-problem-solving implementations of Pengi and the N-Puzzle, and the sociogenesis process occuring in the artificial ant colonies that compose the MANTA project. We then consider a typical strategical game (chess), and see how to decompose it through a distributed reac...

In this article we review knowledge representation formalisms that lend themselves to the representation of capabilities of intelligent agents. The aim of representing capabilities is, of course, that we want to reason about them. The reasoning task we are most interested in is capability brokering, i.e. the task of finding an agent which has a capability that can be used to address a given problem. Thus, the first area we review here is agent cooperation and communication from which the problem originates.