RCal: An Autonomous Agent for Intelligent Distributed Meeting Scheduling

The views and conclusions contained in this document are those of the author and should not be interpreted as representing the official policies or endorsements, either expressed or implied, of Carnegie Mellon University. Abstract Meeting scheduling is an inherently difficult and time consuming task that requires multiple parties to interact and consult their various calendars in order to agree upon a common time. These interactions must take into account numerous constraints that are set by the participants and there is no a-priori knowledge of all the possible constraints that may apply when scheduling a meeting. In addition to this there is an overhead in terms of time and effort involved in scheduling a meeting that can sometime make it impossible to schedule an event, especially if the number of attendees is large. This report details the design and implementation of an intelligent meeting scheduling agent that assists humans in office environments by scheduling meetings. RCal agents negotiate with each other on the behalf of their users and agree on a common meeting time that is acceptable to all the users and abides by all the constraints set by all the attendees. RCal is a distributed problem solver where each RCal agent forms a component of the problem solving engine by proving its own inputs as the problem converges towards a solution. In addition to this RCal is a robust, user-friendly system that integrates well with the latest computing environments and works efficiently to aid the human user in the task of scheduling meetings.