Distributed Artificial Intelligence (DAI) has existed as a subfield of AI for less than two decades. DAI is

Multi-agent domains consisting of teams of agents that need to collaborate in an adversarial environment offer challenging research opportunities. In this article, we introduce periodic team synchronization (PTS) domains as time-critical environments in which agents act autonomously with low communication, but in which they can periodically synchronize in a full-communication setting. The two main contributions of this article are a flexible team agent structure and a method for inter-agent communication in domains with unreliable, single-channel, low-bandwidth communication. First, the novel team agent structure allows agents to capture and reason about team agreements. We achieve collaboration between agents through the introduction of formations. A formation decomposes the task space defining a set of roles. Homogeneous agents can flexibly switch roles within formations, and agents can change formations dynamically, according to pre-defined triggers to be evaluated at run-time. This flexibility increases the performance of the overall team. Our teamwork structure further includes pre-planning for frequent situations. Second, the novel communication method is designed for use during the lowcommunication periods in PTS domains. It overcomes the obstacles to inter-agent communication in multi-agent environments with unreliable, high-cost, low-bandwidth communication. We fully implemented both the flexible teamwork structure and the communication method in the domain of simulated robotic soccer, and conducted controlled empirical experiments to verify their effectiveness. In addition, our simulator team made it to the semi-finals of the RoboCup-97 competition, in which 29 teams participated.

. Adaptation in open, multi-agent information gathering systems is important for several reasons. These reasons include the inability to accurately predict future problem-solving workloads, future changes in existing information requests, future failures and additions of agents and data supply resources, and other future task environment characteristic changes that require system reorganization. We have developed a multi-agent distributed system infrastructure, Retsina (REusable Task Structure-based Intelligent Network Agents) that handles adaptation in an open Internet environment. Adaptation occurs both at the individual agent level as well as at the overall agent organization level. The Retsina system has three types of agents. Interface agents interact with the user receiving user specifications and delivering results. They acquire, model, and utilize user preferences to guide system coordination in support of the user's tasks. Task agents help users perform tasks by formulating p...

Multi-agent domains consisting of teams of agents that need to collaborate in an adversarial environment offer challenging research opportunities. In this paper, we introduce periodic team synchronization domains, as time-critical environments in which agents act autonomously with limited communication, but they can periodically synchronize in a full-communication setting. We present a team agent structure that allows for an agent to capture and reason about team agreements. We achieve collaboration between agents through the introduction of formations. A formation decomposes the task space defininga set of roles. Homogeneous agents

. Hospital Patient Scheduling is an inherently distributed problem because of the way real hospitals are organized. As medical procedures have become more complex, and their associated tests and treatments have become interrelated, the current ad hoc patient scheduling solutions have been observed to break down [23]. We propose a multi-agent solution using the Generalized Partial Global Planning (GPGP) approach that preserves the existing human organization and authority structures, while providing better system-level performance (increased hospital unit throughput and decreased patient stay time). To do this, we extend GPGP with a new coordination mechanism to handle mutually exclusive resource relationships. Like the other GPGP mechanisms, the new mechanism can be applied to any problem with the appropriate resource relationship. We evaluate this new mechanism in the context of the hospital patient scheduling problem, and examine the effect of increasing interrelations between tasks ...

A generic, component based architecture is proposed as a basis for designing the agents used within Multi-Agent Systems. The architecture, based on Sun's Java Beans, is explored, and both domain independent and applied component examples are described in detail. Designs for theoretical new components for the applied agent are also proposed and examined. 1 Overview Component based architectures are a relatively new introduction to software development. They attempt to effectively encapsulate the functionality of an object while respecting interface conventions, the goal being to easily combine groups of components to create stand alone applications. This type of design promotes software reusability - the ability to painlessly transport source code from one project to another - which is a long sought after but infrequently achieved goal of software engineering. In this paper I will describe such a component architecture designed for use in the domain of agent construction. Much of ...

The World Wide Web has become an invaluable information resource but the explosion of available information has made web search a time consuming and complex process. The large number of information sources and their different levels of accessibility, reliability and associated costs present a complex information gathering control problem. This paper describes the rationale, architecture, and implementation of a next generation information gathering system – a system that integrates several areas of Artificial Intelligence research under a single umbrella. Our solution to the information explosion is an information gathering agent, BIG, that plans to gather information to support a decision process, reasons about the resource trade-offs of different possible gathering approaches, extracts information from both unstructured and structured documents, and uses the extracted information to refine its search and processing activities.

Abstract. To scale agent technologies for widespread use in open systems, agents must have an understanding of the organizational context in which they operate. In this paper we focus on the issue of task valuation and action selection in socially situated or organized agents – specifically on the issue of quantifying agent relationships and relating work motivated by different sources. 1

. In this paper, we describe our agent framework and address

Intelligent environments are an interesting development and research application problem for multiagent systems. The functional and spatial distribution of tasks naturally lends itself to a multi-agent model and the existence of shared resources creates interactions over which the agents must coordinate. In the UMASS Intelligent Home project we have designed and implemented a set of distributed autonomous home control agents and deployed them in a simulated home environment. Our focus is primarily on resource coordination, though this project has multiple goals and areas of exploration ranging from the intellectual evaluation of the application as a general MAS testbed to the practical evaluation of our agent building and simulation tools. 1 Introduction The intelligent home project (IHome) at the UMASS multi-agent systems lab is an exploration in the application of multi-agent systems technology to the problem of managing an intelligent environment. We have implemented a sophisticate...