Multiple Representations of Knowledge in a Mechanics Problem-Solver
Abstract
Expert problem-solving programs have focused on working problems which humans consider difficult Oddly, many such problem-solvers could not solve less difficult versions of the problems addressed by their expertise. This shortcoming also contributed to these programs' inability to solve harder problems. To overcome this paradox’ requires multiple representations of knowledge, inferencing schemes for each, and communication schemes between them. This paper presents a program, NEWTON, applying this idea to the domain of simple classical mechanics. NEWTON employs the method of envisionment, whereby simple questions may be answered directly, and plans produced for solving more complex problems. Envisioning enables NEWTON to use qualitative arguments when possible, with resorts to mathematical equations only if the qualitative reasoning fails to produce a solution.
Cite
Text
de Kleer. "Multiple Representations of Knowledge in a Mechanics Problem-Solver." International Joint Conference on Artificial Intelligence, 1977. doi:10.1016/B978-1-4832-1447-4.50009-2Markdown
[de Kleer. "Multiple Representations of Knowledge in a Mechanics Problem-Solver." International Joint Conference on Artificial Intelligence, 1977.](https://mlanthology.org/ijcai/1977/dekleer1977ijcai-multiple/) doi:10.1016/B978-1-4832-1447-4.50009-2BibTeX
@inproceedings{dekleer1977ijcai-multiple,
title = {{Multiple Representations of Knowledge in a Mechanics Problem-Solver}},
author = {de Kleer, Johan},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {1977},
pages = {299-304},
doi = {10.1016/B978-1-4832-1447-4.50009-2},
url = {https://mlanthology.org/ijcai/1977/dekleer1977ijcai-multiple/}
}