P
Pauline M. Berry
Researcher at SRI International
Publications - 26
Citations - 839
Pauline M. Berry is an academic researcher from SRI International. The author has contributed to research in topics: Two-level scheduling & Dynamic priority scheduling. The author has an hindex of 11, co-authored 26 publications receiving 809 citations. Previous affiliations of Pauline M. Berry include Artificial Intelligence Center.
Papers
More filters
Journal ArticleDOI
PTIME: Personalized assistance for calendaring
TL;DR: The models and technical advances required to satisfy the competing needs of preference modeling and elicitation, constraint reasoning, and machine learning are described and a multifaceted evaluation of the perceived usefulness of the PTIME system is reported.
Journal ArticleDOI
An Intelligent Personal Assistant for Task and Time Management
Karen L. Myers,Pauline M. Berry,Jim Blythe,Ken Conley,Melinda T. Gervasio,Deborah L. McGuinness,David N. Morley,Avi Pfeffer,Martha E. Pollack,Milind Tambe +9 more
TL;DR: An intelligent personal assistant that has been developed to aid a busy knowledge worker in managing time commitments and performing tasks and is highly user centric in its support for human needs, responsiveness to human inputs, and adaptivity to user working style and preferences.
Proceedings ArticleDOI
Deploying a personalized time management agent
Pauline M. Berry,Bart Peintner,Ken Conley,Melinda T. Gervasio,Tomás E. Uribe,Neil Yorke-Smith +5 more
TL;DR: This report on the ongoing practical experience in designing, implementing, and deploying PTIME, a personalized agent for time management and meeting scheduling in an open, multi-agent environment, which advances basic solutions to the fundamental problems.
Journal ArticleDOI
Interactive Execution Monitoring of Agent Teams
TL;DR: A monitoring framework for integrating many domain-specific and task-specific monitoring techniques and then using the concept of value of an alert to avoid operator overload is described, using an execution monitoring approach used to implement Execution Assistants in two different dynamic, data-rich, real-world domains to assist a human in monitoring team behavior.
Journal ArticleDOI
Interactive execution monitoring of agent teams
TL;DR: In this paper, the authors present a domain-independent categorization of the types of alerts a plan-based monitoring system might issue to a user, where each type generally requires different monitoring techniques.