Watch what I do: programming by demonstration
Watch what I do: programming by demonstration
A Small Matter of Programming: Perspectives on End User Computing
A Small Matter of Programming: Perspectives on End User Computing
Information technology and economic performance: A critical review of the empirical evidence
ACM Computing Surveys (CSUR)
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2
Task learning by instruction in tailor
Proceedings of the 10th international conference on Intelligent user interfaces
PLOW: a collaborative task learning agent
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
POIROT: integrated learning of web service procedures
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Journal of Artificial Intelligence Research
Lowering the barriers to website testing with CoTester
Proceedings of the 15th international conference on Intelligent user interfaces
No Code Required: Giving Users Tools to Transform the Web
No Code Required: Giving Users Tools to Transform the Web
How to serve soup: interleaving demonstration and assisted editing to support nonprogrammers
Proceedings of the 16th international conference on Intelligent user interfaces
LiveAction: Automating Web Task Model Generation
ACM Transactions on Interactive Intelligent Systems (TiiS)
Hi-index | 0.00 |
Numerous techniques exist to help users automate repetitive tasks; however, none of these methods fully support end-user creation, use, and modification of the learned tasks. We present an integrated task learning system (ITL) that learns executable procedures based on user demonstration and instruction, constituting a first step toward a broader solution for procedure management. We discuss our deployment of ITL into a collaborative command-and-control system. In this complex domain, ITL's performance with end users doing real tasks indicates that providing multiple, integrated learning techniques both extends functionality and improves user experience. Our experience in integrat-ing this system also provides key insights for future designs of domain-independent task learning systems, specifically in supporting users' ability to understand and edit lengthy procedures.