| Learning Hierarchical Task Models by Defining and Refining Examples |
| Citation: |
Garland, A.; Ryall, K.; Rich, C., "Learning Hierarchical Task Models by Defining and Refining Examples", ACM International Conference on Knowledge Capture (KCAP), ISBN: 1-58113-380-4, pps 44-51, October 2001 (Proc ACM Press) |
| Date: | August 2001 |
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. |
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