Software Engineering White Papers
Learning Hierarchical Task Models by Defining and Refining Examples
Overview Task models are used in many areas of computer science including planning, intelligent tutoring, plan recognition, interface design, and decision theory. However, developing task models is a significant practical challenge. We present a task model development environment centered around a machine learning engine that infers task models from examples. A novel aspect of the environment is support for a domain expert to refine past examples as he or she develops a clearer understanding of how to model the domain. Collectively, these examples constitute a "test suite" that the development environment manages in order to verify that changes to the evolving task model do not have unintended consequences.
| Publisher | Mitsubishi Electric Research Laboratories (MERL) | File Format | PDF, requires Acrobat Rdr 5 |
|---|---|---|---|
| Date Published | August 2001 | Downloads | 2 |
| Format | White Papers | ||
| Topics | |||
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