Integrating Task Learning Tools to Support End Users in Real-World Applications

Aaron Spaulding, Jim Blythe, Will Haines, Melinda Gervasio
International Conference on Intelligent User Interfaces (IUI), 2009.

Abstract

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 integrating 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.

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Jim Blythe