Worth Fixing: Personalizing Maintenance Alerts for Optimal Performance

This work was presented at HAIDM 2015. The 2015 workshop on Human-Agent Interaction Design and Models was co-organised by SmartSociety.

Abstract: Preventive maintenance is essential for the smooth operation of any equipment. Still, people occasionally do not maintain their equipment adequately. Alert systems attempt to remind people to perform maintenance. However, most of these systems do not provide alerts at the optimal timing, and nor do they take into account the time required for maintenance or compute the optimal timing for a specific user. In this paper we model the problem of maintenance performance, assuming maintenance is time consuming. We solve the optimal policy for the user, i.e., the optimal timing for a user to perform maintenance. This optimal strategy depends on the user’s value of time, and thus it may vary from user to user and may change over time. Based on the solved optimal strategy we present a personalized alert agent, which, depending on the user’s value of time, alerts the user when she should perform maintenance. In an experiment using a spaceship computer game, we show that receiving alerts from the personalized alert agent significantly improves user performance.

Citation: Avraham Shvartzon, Amos Azaria, Sarit Kraus, Claudia Goldman, Joachim Meyer and Omer Tsimhoni. Worth Fixing: Personalizing Maintenance Alerts for Optimal Performance.

Download: http://bit.ly/1WcKUVa

About P. Andreadis

Pre-Doctoral Research Assistant in AI and Social Computation @ University of Edinburgh.

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