Artificial Intelligence - Special volume on planning and scheduling
A Methodology for Testing Intrusion Detection Systems
IEEE Transactions on Software Engineering
Predicting the effects of in-car interfaces on driver behavior using a cognitive architecture
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Active preference learning for personalized calendar scheduling assistance
Proceedings of the 10th international conference on Intelligent user interfaces
Exploring the constraints of human behavior representation
WSC '04 Proceedings of the 36th conference on Winter simulation
Two Issues for an Ambient Reminding System: Context-Awareness and User Feedback
Proceedings of the 2007 conference on Advances in Ambient Intelligence
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We describe a simulation system that models the user of a calendar-management tool. The tool is intended to learn the user's scheduling preferences, and we employ the simulator to evaluate learning strategies. The simulated user is instantiated with a set of preferences over local and global features of a schedule such as the level of importance of a particular meeting and the amount of preparation time available before it is to begin. The system then processes a set of simulated meeting requests, and over time and through user feedback, it learns the user's preferences, affording it the ability to thereafter manage the user's schedule more autonomously.