language: en

Humans Plus Agents Maintain Schedules Better than Either Alone

Tim Oates and Paul R. Cohen
Computer Science Technical Report 94-03
Experimental Knowledge Systems Laboratory Department of Computer Science, Box 34610 Lederle Graduate Research Center University of Massachusetts
Amherst, MA 01003-4610

Abstract Tracking and evaluating the progress of large, complex plans or schedules as they unfold in real time is extremely difficult for humans. In this paper we present a mixed-initiative system for the task of schedule maintenance in a simulated shipping network. A schedule maintenance agent monitors the network, predicting the occurrence of states that may result in reduced throughput and formulating schedule modifications to avoid those states. The goal is to maximize throughput while minimizing disruptions to the original schedule. We present results of experiments in which human subjects attempt to obtain that goal both with and without the aid of the agent. We found that the human and the agent working together are able to achieve better results than either one working alone. In addition to looking at global performance measures such as throughput, we analyze individual schedule modification decisions made by subjects in an attempt to assign credit for the improvements in performance.

[This research is supported by ARPA-AFOSR contract F30602-91-C-0076.]