Interface agents as surrogate users

intelligence ◽  
2000 ◽  
Vol 11 (2) ◽  
pp. 28-38 ◽  
Author(s):  
Robert St. Amant
Keyword(s):  
1996 ◽  
Vol 05 (02n03) ◽  
pp. 181-211 ◽  
Author(s):  
KATIA SYCARA ◽  
DAJUN ZENG

We are investigating techniques for developing distributed and adaptive collections of information agents that coordinate to retrieve, filter and fuse information relevant to the user, task and situation, as well as anticipate user's information needs. In our system of agents, information gathering is seamlessly integrated with decision support. The task for which particular information is requested of the agents does not remain in the user's head but it is explicitly represented and supported through agent collaboration. In this paper we present the distributed system architecture, agent collaboration interactions, and a reusable set of software components for structuring agents. The system architecture 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 problem solving plans and carrying out these plans through querying and exchanging information with other software agents. Information agents provide intelligent access to a heterogeneous collection of information sources. We have implemented this system framework and are developing collaborating agents in diverse complex real world tasks, such as organizational decision making, investment counseling, health care and electronic commerce.


Author(s):  
ELHADI SHAKSHUKI ◽  
HAMADA GHENNIWA ◽  
MAHAMED KAMEL

The rapid growth of the network-centered (Internet and Intranet) computing environments requires new architectures for information gathering systems. Typically, in these environments, the information resources are dynamic, heterogeneous and distributed. In addition, these computing environments are open, where information resources may be connected or disconnected at any time. This paper presents an architecture for a multi-agent information gathering system. The architecture includes three types of agents: interface, broker and resource agents. The interface agents interact with the users to fulfill their interests and preferences. The resource agents access and capture the content of the information resources. The broker agents facilitate cooperation among the information and the resource agents to achieve their desired goals. This paper provides the agents' architecture, design and implementations that enable them to cooperate, coordinate and communicate with each other to gather information in an open and dynamic environment.


2000 ◽  
Vol 2 (1) ◽  
pp. 16-26 ◽  
Author(s):  
R. J. Keeble ◽  
R. D. Macredie ◽  
D. S. Williams

Author(s):  
Elisabeth Andr√© ◽  
Matthias Rehm
Keyword(s):  

Author(s):  
Alexander Serenko

This chapter reports on an empirical investigation of user perceptions of the importance of several characteristics of interface agents. Interface agents are software entities that are incorporated in various computer applications including electronic mail systems. As evidenced by the growing body of empirical studies and the increasing number of interface agent-based applications on the software market, there is a strong need for the development of this technology. According to a meta-review of agent-related literature by Dehn and van Mulken (2000), there are several characteristics of interface agents that require special attention from agent developers. However, prior to this study, the importance of these characteristics from the end-user perspective remained unclear. In order to identify the significance of these characteristics, a group of the actual users of an email interface agent was surveyed. The results indicate that information accuracy and the degree of the usefulness of an agent are the most salient factors, followed by user comfortability with an agent, the extent of user enjoyment, and visual attractiveness of an agent. The implications of the findings for both theory and practice are discussed.


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