Collaborative interface agents

Yezdi Lashkari, Max Metral, Pattie Maes

1994 · 358 citations · 9 references

TL;DR

Interface agents are semi‑intelligent systems that assist users with daily computer tasks, and recent research has proposed learning‑based approaches with demonstrated prototypes. The authors propose a multi‑agent collaboration framework to reduce the time required for learning and expand agents’ capabilities beyond observed actions. Agents learn by observing users and detecting behavioral patterns, and the framework is implemented and tested with a prototype that handles electronic mail. Learning agents initially take time to become useful and can only perform actions they have seen the user perform.

Abstract

Interface agents are semi-intelligent systems which assist users with daily computer-based tasks. Recently, various researchers have proposed a learning approach towards building such agents and some working prototypes have been demonstrated. Such agents learn by 'watching over the shoulder' of the user and detecting patterns and regularities in the user's behavior. Despite the successes booked, a major problem with the learning approach is that the agent has to learn from scratch and thus takes some time becoming useful. Secondly, the agent's competence is necessarily limited to actions it has seen the user perform. Collaboration between agents assisting different users can alleviate both of these problems. We present a framework for multi-agent collaboration and discuss results of a working prototype, based on learning agents for electronic mail.

References

9