Multi-agent Meeting Scheduling Using Mobile Context

Abstract

Despite the use of newer and more powerful calendar and collaboration tools, the task of scheduling and rescheduling meetings is very time consuming for busy professionals, especially for highly mobile people. Research projects and commercial calendar products have worked since the early 1990s on implementing intelligent meeting organizers to automate meeting scheduling. However, automated schedulers have not been widely accepted or used by professionals around the world. Our research shows that the task of organizing meeting can be improved by reducing the scheduling workload and making meeting logistics more efficient. For example, new tools can decide meeting venues and dynamically handle exceptions, such as one participant not being able to arrive at the meeting location on time. In this paper, we discuss a solution to effectively employ the mobile user’s context in making more intelligent decisions on behalf of the user. Business Meeting Organizer (BMO) is a multi-agent meeting scheduling system, designed to automate time and venue decisions and to handle exceptions. Rather than using a traditional multi-user calendar-based scheduler, BMO has representatives (“software secretaries” implemented as software agents) for each user to negotiate a best time for a particular meeting, taking into account availability, context and preferences. Several technologies are used by BMO to provide secure and intelligent meeting scheduling functionality. By using agent technology, BMO keeps private calendar information invisible to other meeting participants and allows diverse intelligent negotiation and scheduling policies to be employed. Through the use of a rules engine, BMO can consider meeting participants’ personal preferences as to when to schedule the meeting. By means of mobile devices, BMO can get the user’s context information, such as the user’s physical location, which may be helpful in deciding the meeting venue and handling other meeting issues. In this paper, we discuss a solution to effectively employ the user’s mobile context information in making more intelligent decisions on behalf of the user.