A formal theory of plan recognition
A formal theory of plan recognition
Detection of abrupt changes: theory and application
Detection of abrupt changes: theory and application
Watch what I do: programming by demonstration
Watch what I do: programming by demonstration
Eager: programming repetitive tasks by demonstration
Watch what I do
New directions in AI planning
Building applications using only demonstration
IUI '98 Proceedings of the 3rd international conference on Intelligent user interfaces
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Programming by Demonstration Using Version Space Algebra
Machine Learning
Learning programs from traces using version space algebra
Proceedings of the 2nd international conference on Knowledge capture
Sheepdog: learning procedures for technical support
Proceedings of the 9th international conference on Intelligent user interfaces
Field studies of computer system administrators: analysis of system management tools and practices
CSCW '04 Proceedings of the 2004 ACM conference on Computer supported cooperative work
DocWizards: a system for authoring follow-me documentation wizards
Proceedings of the 18th annual ACM symposium on User interface software and technology
Augmentation-based learning: combining observations and user edits for programming-by-demonstration
Proceedings of the 11th international conference on Intelligent user interfaces
Proceedings of the 12th international conference on Intelligent user interfaces
Universal plans for reactive robots in unpredictable environments
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 2
Similarity-based alignment and generalization
ECML'05 Proceedings of the 16th European conference on Machine Learning
Error bounds for convolutional codes and an asymptotically optimum decoding algorithm
IEEE Transactions on Information Theory
Input-output HMMs for sequence processing
IEEE Transactions on Neural Networks
TellMe: learning procedures from tutorial instruction
Proceedings of the 16th international conference on Intelligent user interfaces
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We introduce parallel collaborative programming-by-demonstration (PBD) as a principled approach to capturing knowledge on how to perform computer-based procedures by independently recording multiple experts executing these tasks and combining the recordings via a learning algorithm. Traditional PBD has focused on end-user programming for a single user, and does not support parallel collaborative procedure model construction from examples provided by multiple experts. In this paper we discuss how to extend the main aspects of PBD (instrumentation, abstraction, learning, and execution), and we describe the implementation of these extensions in a system called Sheepdog.