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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

ion and delegation: Agents can be made extensible and composable in ways that common iconic interface objects cannot. Because we can "communicate" with them, they can share our goals, rather than simply process our commands. They can show us how to do things and tell us what went wrong (Miller and Neches 1987). . Flexibility and opportunism: Because they can be instructed at the level of 16 BRADSHAW goals and strategies, agents can find ways to "work around" unforeseen problems and exploit new opportunities as they help solve problems. . Task orientation: Agents can be designed to take the context of the person's tasks and situation into account as they present information and take action. . Adaptivity: Agents can use learning algorithms to continually improve their behavior by noticing recurrent patterns of actions and events. Toward Agent-Enabled System Architectures In the future, assistant agents at the user interface and resource-managing agents behind the scenes will increas...

physics-based modeling Abstract: This paper proposesa framework for animation that can achieve the intricacy of motion evident in certain natural ecosystems with minimal input from the animator. The realistic appearance, movement, and behavior of individual animals, as well as the patterns of behavior evident in groups of animals fall within the scope of the framework. Our approach to emulating this level of natural complexity is to model each animal holistically as an autonomous agent situated in its physical world. To demonstrate the approach, we develop a physics-based, virtual marine world. The world is inhabited by artificial fishes that can swim hydrodynamically in simulated water through the motor control of internal muscles that motivate fins. Their repertoire of behaviors relies on their perception of the dynamic environment. As in nature, the detailed motions of artificial fishes in their virtual habitat are not entirely predictable because they are not scripted. 1

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This paper develops artificial life patterned after animals as evolved as those in the superclass Pisces. It demonstrates a virtual marine world inhabited by realistic artificial fishes. Our algorithms emulate not only the appearance, movement, and behavior of individual animals, but also the complex group behaviors evident in many aquatic ecosystems. We model each animal holistically. An artificial fish is an autonomous agent situated in a simulated physical world. The agent has (i) a three-dimensional body with internal muscle actuators and functional fins, which deforms and locomotes in accordance with biomechanic and hydrodynamic principles, (ii) sensors, including eyes that can image the environment, and (iii) a brain with motor, perception, behavior, and learning centers. Artificial fishes exhibit a repertoire of piscine behaviors that rely on their perceptual awareness of their dynamic habitat. Individual and emergent collective behaviors include caudal and pectoral loc...

We propose an agent-based framework for assisting and simplifying person-to-person communication for information gathering tasks. As an example, we focus on locating experts for any specified topic. In our approach, the informal person-to-person networks that exist within an organization are used to "referral chain" requests for expertise. User-agents help automate this process. The agents generate referrals by analyzing records of email communication patterns. Simulation results show that the higher responsiveness of an agent-based system can be effectively traded for the higher accuracy of a completely manual approach. Furthermore, preliminary experience with a group of users on a prototype system has shown that useful automatic referrals can be found in practice. Our experience with actual users has also shown that privacy concerns are central to the successful deployment of personal agents: an advanced agent-based system will therefore need to reason about issues involving trust an...

this paper [4] and it is further developed in [5].

construction system. Its primary component is the basic software agent --- a computational framework for building agents which is essentially an agent operating system. We also present a new language for programming the basic software agent whose primitives are designed around human-level descriptions of agent activity. Via this programming language, users can easily implement a wide-range of typical software agent applications, e.g. personal on-line assistants and meeting scheduling agents. The SodaBot system has been implemented and tested, and its description comprises the bulk of this thesis.

Abstract not found