Knowledge Refinement Using a High Level, Non-Technical Vocabulary

Abstract

Current knowledge acquisition tools force users to enter knowledge in the low-level operational vocabulary of the system being constructed. We describe an incremental, model-based approach to knowledge acquisition that addresses this problem. Users can present knowledge in a flexible, culturally-shared vocabulary of planning concepts. Our approach is implemented in BRAINSTORMER, a planner that takes advice in the context of ongoing problem solving.

Cite

Text

Jones. "Knowledge Refinement Using a High Level, Non-Technical Vocabulary." International Conference on Machine Learning, 1991. doi:10.1016/B978-1-55860-200-7.50008-8

Markdown

[Jones. "Knowledge Refinement Using a High Level, Non-Technical Vocabulary." International Conference on Machine Learning, 1991.](https://mlanthology.org/icml/1991/jones1991icml-knowledge/) doi:10.1016/B978-1-55860-200-7.50008-8

BibTeX

@inproceedings{jones1991icml-knowledge,
  title     = {{Knowledge Refinement Using a High Level, Non-Technical Vocabulary}},
  author    = {Jones, Eric K.},
  booktitle = {International Conference on Machine Learning},
  year      = {1991},
  pages     = {18-22},
  doi       = {10.1016/B978-1-55860-200-7.50008-8},
  url       = {https://mlanthology.org/icml/1991/jones1991icml-knowledge/}
}