International Journal on Artificial Intelligence Tools

In this paper we describe a paradigm for content-focused matchmaking, based on a recently proposed model for constraint acquisition and satisfaction. Matchmaking agents are constraint-based solvers that interact with other, possibly human, agents (Customers). The Matchmaker provides potential solutions ("suggestions") based on partial knowledge, while gaining further information about the problem itself from the other agent through the latter's evaluation of these suggestions. The dialogue between Matchmaker and Customer results in iterative improvement of solution quality, as demonstrated in simple simulations. We also show empirically that this paradigm supports "suggestion strategies" for finding acceptable solutions more efficiently or for increasing the amount of information obtained from the Customer. This work also indicates some ways in which the tradeoff between these two metrics for evaluating performance can be handled.

With the exponential growth of the Internet, information seekers are faced with the so-called problem of information overload. Adaptive Information Agents have been developed to alleviate this problem. The Main issues in the development of these agents are document representation, learning, and classification. Various paradigms have been explored for the development of adaptive information agents, and the performance of these agents differs in terms of computational efficiency, classification effectiveness, learning autonomy, exploration capability, and explanatory power. To develop a basic under-standing of the pros and cons of these paradigms, some representative information agents are examined. Such a review also serves to identify a general for the development of the next generation adaptive information agents.

Distributed database techniques and the Internet provide producers of statistics with a means to publish their data and metadata widely and make them available to a variety of users. Data matching to a user query and data access as well as data harmonization are some of the problems that should be solved. Intelligence is required in various stages of query answering and data matching. Moreover, the breadth and distributed nature of the Internet urge for a distributed approach. Agents seem to be the means by which both intelligence and distributed processing can be achieved. This paper presents a distributed approach for answering queries on statistical data that exist over the Internet using a multi-agent framework.

The number and size of information services available on the internet has been growing exponentially over the past few years. This growth has created an urgent need for information agents that act as brokers in the sense that they can autonomously search, gather, and integrate information on behalf of a user. To remain useful, such brokers will have to evolve throughout their lifetime to keep up with evolving and ever-changing information services. This paper proposes a framework named XIB (eXtensible Information Brokers) for building and evolving information brokers.

The XIB takes as input a description of required information services and supports the interactive generation of an integrated query interface. It also generates wrappers for each information service dynamically. Once the query interface and wrappers are in place, the user can specify a query and get back a result which integrates data from all wrapped information sources. The XIB depends heavily on XML-related techniques. More specifically, we use DTDs to model the input and output of each service, and XML to represent both input and output values. Based on such representations, the paper investigates service integration in the form DTD integration, and studies query decomposition in the form of XML element decomposition. Within the proposed framework, it is easy to add or remove information services to a broker, thereby facilitating maintenance, evolution and customization of information brokers.

The Internet is a vast, semi-structured information repository that is expanding ever-faster with two alarming results. First, finding information is becoming increasingly difficult, and second, the management of such information resources is also becoming more complex. We have developed an Intelligent Distributed Information Management System (IDIoMS) to solve these problems. IDIoMS provides a comprehensive set of tools for personalized information delivery, and a platform that enables straightforward management of distributed information resources using agent technologies. These agents enable the sharing, management, search, and presentation of useful information that is widely distributed over a network such as the Internet. IDIoMS benefits users through the automatic provision of timely and relevant information with minimal need for users to search for that information. In addition, the system also benefits service providers through the plug-and-play provision of information services that minimizes the overhead needed to make their service widely available. This paper describes the concept and the architecture of IDIoMS and discusses its utility through three field trials.

In this paper, an agent architecture is proposed that can be used to integrate pre-existing components that provide the domain dependent agent functionality. The key integrating feature of the agent is an active message board that is used for inter-component, hence intra-agent communication. The board is active because it automatically forwards messages to components, they do not have to poll the message board. It does this on the basis of message pattern functions that components place on the board using advertisement messages. These functions can contain component provided semantic tests on the content of the message, they can also communicate with any other component whilst they are being applied. In addition an agent management toolkit, called ALFA, is described which offers a set of agent management services. This toolkit consists of a number of servers for storing the code of the components and symbolic descriptions of what agents regarding their component makeup. A third server uses all this information to facilitate launching new agents. Two prototype systems are also presented where the presented infrastructure has been applied. The one involves an agent based system used to control the environmental conditions in a building and the second is an agent based network management application.