Collaborative plans for complex group action
Artificial Intelligence
An interactive constraint-based system for drawing graphs
Proceedings of the 10th annual ACM symposium on User interface software and technology
Three levels of end-user tailoring: customization, integration, and extension
Computers and design in context
Proceedings of the third annual conference on Autonomous Agents
Principles of mixed-initiative user interfaces
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Introduction: personalized views of personalization
Communications of the ACM
Experience with personalization of Yahoo!
Communications of the ACM
Communications of the ACM
Communications of the ACM
A writer's collaborative assistant
Proceedings of the 7th international conference on Intelligent user interfaces
Interpreting Information Requests in Context A Collaborative Web Interface for Distance Learning
Autonomous Agents and Multi-Agent Systems
Knowledge representation and open world planning using psi-forms
Knowledge representation and open world planning using psi-forms
A machine learning approach to web personalization
A machine learning approach to web personalization
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We present a novel method for software personalization. Personalization is understood broadly as a set of mechanisms by which an application is tailored to a particular end user and his or her task. The presented method outlined here is motivated by and remedies a few widely recognized problems in the way customization is carried out. The proposed method has been used in a collaborative system called Writer's Aid. Itrelies on a declarative specification of preconditions and effects of system's actions and applies artificial intelligence, automated reasoning, and planning framework and techniques to dynamically recognize the lack or availability of the personal information at the precise time when it affects a system action and initiates an interaction with the user aimed at eliciting this information in case it has not yet been specified.