An architecture for cooperative information systems

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Abstract

With the fast growth of the information space in the Internet and large-scale Intranet computing environments, a new design paradigm is required for information systems. In such environments, the amount, the dynamic, the heterogeneity and the distributed nature of the information make it difficult for a user to locate and retrieve the desired information. Moreover, these computing environments are open environments, where the information resources may join or disjoin at anytime. To this end, this paper proposes a multi-agent multi-tier architecture. These agents are autonomous and goal driven agents that cooperatively assist different users to locate and retrieve information from distributed resources. The system architecture comprises of three tiers. At the front end, User Agents interact with the users to fulfill their interests and preferences. At the back end, Resource Agents access and capture the content and changes of the information resources. At the middle tier, Broker Agents facilitate cooperation among the agents. A prototype of this system is implemented to demonstrate how the agents can transparently cooperate to locate and retrieve information from dynamic and distributed information resources.

Introduction

To date, there is a substantial growth of information in the Internet and Intranet-based systems. However, before any value can be generated from these systems, several design issues need to be addressed such as the distributed and the dynamic nature of the environment, and the large size of the information. These make it difficult for a user to locate the relevant information. In addition to that, in open environment, information resources may join or disjoin at anytime.

One promising solution is agent-orientation as a design paradigm. In our work [9], we developed a Coordinated Intelligent Rational Agent (CIR-Agent) model for cooperative distributed systems. This model provides an integrated solution for the main design issues such as autonomy, heterogeneity and transparency. For example, autonomy incorporated by modeling an agent as an independent proactive entity that has the ability to make decisions concerning its own actions without any external interference. Furthermore, the existence of the agent is not justified by the existence of other agents. Heterogeneity is dealt with by modeling an agent as a goal driven entity. This allows agents to interact with each other at the ‘goal level’ and hides the internal structure of the agents. Transparency is achieved by modeling an agent as a cooperative, coordinated agent that is capable of constructing connections with other agents.

This paper describes a multi-agent system that acts as a mediator between the user and the information environment. It helps the user to locate and retrieve information. These agents interact cooperatively in a distributed environment and collectively achieve the following: (1) provide the users with an integrated view of information, (2) proactively search for information from local and/or remote distributed sources and avoiding repetitive users intervention to satisfy their interest, (3) customize the information to make it relevant to the user's interest, (4) monitor and update the changes of the information resources, and (5) provide an answer within a bounded time.

The remaining of this paper is organized as follows. Section 2 describes the proposed system architecture. Section 3 details the implementation of the system, followed by experimental results in Section 4. Related work is discussed in Section 5. Section 6 presents the conclusions.

Section snippets

System architecture

The architecture of the proposed agent-based system is designed to help users to locate and retrieve information from distributed resources. Each agent is autonomous, cooperative, coordinated, intelligent, rational and able to communicate with other agents to fulfill the users' needs. Fig. 1 shows the three types of the agent functionality in the proposed three-tier architecture. At the front-end of the system, the agents (User Agents) keep track of the users' interest and preferences. At the

Implementation

The proposed system has been implemented using Java and the IBM Agent Builder Environment (ABE) [1]. The ABE supports a rule-based, forward chaining inference engine that is used as the reasoning mechanism. The knowledge base representation is based on Knowledge Interchange Format (KIF) [8]. The agent's components are implemented to function in parallel and in multi-tasking fashion using explicit thread management. This allows an agent to be involved in concurrent interaction with more than one

Experimental results

In this section, two examples were constructed and used to demonstrate how the agents of the proposed system interact with each other to handle a user query. The first example is used to evaluate the performance of the system for its ability to adapt the user's topic of interest. The second example is used to demonstrate the ability of the system to cope with open environments and how the system performance is improved in terms of computational time. Towards this end, we implemented two User

Related work

The rapid growth of the network-centered (Internet and large-scale Intranet) information computing environments has made a significant contribution to the problem of providing an easy way to assist users to locate and retrieve information from multiple information resources that might be heterogeneous.

Researchers in Ref. [14] have developed an agent that assist a group of people in browsing, by suggesting new material that is likely to be of common interest. In this approach, the information is

Conclusions

Recently, agent-based technology has become a promising design paradigm and has a growing appeal for a variety of applications of distributed systems. This paper proposed a multi-agent system that is based on autonomous and heterogeneous architecture. This system assists users in the process of locating and retrieving information from distributed information systems. It acts as a mediator between the user and the information environment. The system is layered into multi-tier architecture. At

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